The diagram below shows the various functions in the metafor package (and how they are related to each other). If the package is installed, you should also be able to open this diagram directly from R with the command vignette("diagram"). The image below should also be clickable (to see a larger version of it).
+
The diagram below shows the various functions in the metafor package (and how they are related to each other). If the package is installed, you should also be able to open this diagram directly from R with the command vignette("diagram"). The image below should also be clickable (to see a larger version of it).
the predict.rma() and predict.rma.ls() functions now also accept a matrix as input that includes a column for the intercept term (in which case the intercept argument is ignored)
+
metafor 4.7-24 (2024-07-09)
+
added collapse argument to the various cumul() functions
+
the predict.rma() and predict.rma.ls() functions now also accept a matrix as input that includes a column for the intercept term (in which case the intercept argument is ignored)
added pairwise() function to construct a matrix of pairwise contrasts
anova() and predict() gain adjust argument for adjusting p-values / interval bounds for multiple testing
vector with the values at which the polygons should be drawn.
-
vi
+
vi
vector with the corresponding variances.
-
sei
+
sei
vector with the corresponding standard errors (note: only one of the two, vi or sei, needs to be specified).
-
ci.lb
+
ci.lb
vector with the corresponding lower confidence interval bounds. Not needed if vi or sei is specified. See ‘Details’.
-
ci.ub
+
ci.ub
vector with the corresponding upper confidence interval bounds. Not needed if vi or sei is specified. See ‘Details’.
-
pi.lb
+
pi.lb
optional vector with the corresponding lower prediction interval bounds.
-
pi.ub
+
pi.ub
optional vector with the corresponding upper prediction interval bounds.
-
rows
+
rows
vector to specify the rows (or more generally, the horizontal positions) for plotting the polygons (defaults is -1). Can also be a single value to specify the row (horizontal position) of the first polygon (the remaining polygons are then plotted below this starting row).
-
level
+
level
optional numeric value between 0 and 100 to specify the confidence interval level (see here for details).
-
annotate
+
annotate
optional logical to specify whether annotations should be added to the plot for the polygons that are drawn.
-
digits
+
digits
optional integer to specify the number of decimal places to which the annotations should be rounded.
-
width
+
width
optional integer to manually adjust the width of the columns for the annotations.
-
mlab
+
mlab
optional character vector with the same length as x giving labels for the polygons that are drawn.
-
transf
+
transf
optional argument to specify a function to transform the x values and confidence interval bounds (e.g., transf=exp; see also transf).
-
atransf
+
atransf
optional argument to specify a function to transform the annotations (e.g., atransf=exp; see also transf).
-
targs
+
targs
optional arguments needed by the function specified via transf or atransf.
-
efac
+
efac
optional vertical expansion factor for the polygons.
-
col
+
col
optional character string to specify the color of the polygons.
-
border
+
border
optional character string to specify the border color of the polygons.
-
lty
+
lty
optional character string to specify the line type for the prediction interval.
-
fonts
+
fonts
optional character string to specify the font for the labels and annotations.
-
cex
+
cex
optional symbol expansion factor.
-
constarea
+
constarea
logical to specify whether the height of the polygons (when adding multiple) should be adjusted so that the area of the polygons is constant (the default is FALSE).
Add Polygons to Forest Plots (Method for 'predict.rma' Objects)
Arguments
-
x
+
+
x
an object of class "predict.rma".
-
rows
+
rows
vector to specify the rows (or more generally, the horizontal positions) for plotting the polygons (defaults is -2). Can also be a single value to specify the row (horizontal position) of the first polygon (the remaining polygons are then plotted below this starting row).
-
annotate
+
annotate
optional logical to specify whether annotations should be added to the plot for the polygons that are drawn.
-
addpred
+
addpred
logical to specify whether the bounds of the prediction interval should be added to the plot (the default is FALSE).
-
digits
+
digits
optional integer to specify the number of decimal places to which the annotations should be rounded.
-
width
+
width
optional integer to manually adjust the width of the columns for the annotations.
-
mlab
+
mlab
optional character vector with the same length as x giving labels for the polygons that are drawn.
-
transf
+
transf
optional argument to specify a function to transform the x values and confidence interval bounds (e.g., transf=exp; see also transf).
-
atransf
+
atransf
optional argument to specify a function to transform the annotations (e.g., atransf=exp; see also transf).
-
targs
+
targs
optional arguments needed by the function specified via transf or atransf.
-
efac
+
efac
optional vertical expansion factor for the polygons.
-
col
+
col
optional character string to specify the color of the polygons.
-
border
+
border
optional character string to specify the border color of the polygons.
-
lty
+
lty
optional character string to specify the line type for the prediction interval.
-
fonts
+
fonts
optional character string to specify the font for the labels and annotations.
-
cex
+
cex
optional symbol expansion factor.
-
constarea
+
constarea
logical to specify whether the height of the polygons (when adding multiple) should be adjusted so that the area of the polygons is constant (the default is FALSE).
Aggregate Multiple Effect Sizes or Outcomes Within Studies
-
+
aggregate.escalc.Rd
@@ -95,7 +95,7 @@
Aggregate Multiple Effect Sizes or Outcomes Within Studies
-
# S3 method for escalc
+
# S3 method for class 'escalc'aggregate(x, cluster, time, obs, V, struct="CS", rho, phi, weighted=TRUE, checkpd=TRUE, fun, na.rm=TRUE, addk=FALSE, subset, select, digits, var.names, ...)
@@ -103,58 +103,59 @@
Aggregate Multiple Effect Sizes or Outcomes Within Studies
Arguments
-
x
+
+
x
an object of class "escalc".
-
cluster
+
cluster
vector to specify the clustering variable (e.g., study).
-
time
+
time
optional vector to specify the time points (only relevant when struct="CAR", "CS+CAR", or "CS*CAR").
-
obs
+
obs
optional vector to distinguish different observed effect sizes or outcomes measured at the same time point (only relevant when struct="CS*CAR").
-
V
+
V
optional argument to specify the variance-covariance matrix of the sampling errors. If unspecified, argument struct is used to specify the variance-covariance structure.
-
struct
+
struct
character string to specify the variance-covariance structure of the sampling errors within the same cluster (either "ID", "CS", "CAR", "CS+CAR", or "CS*CAR"). See ‘Details’.
-
rho
+
rho
value of the correlation of the sampling errors within clusters (when struct="CS", "CS+CAR", or "CS*CAR"). Can also be a vector with the value of the correlation for each cluster.
-
phi
+
phi
value of the autocorrelation of the sampling errors within clusters (when struct="CAR", "CS+CAR", or "CS*CAR"). Can also be a vector with the value of the autocorrelation for each cluster.
-
weighted
+
weighted
logical to specify whether estimates within clusters should be aggregated using inverse-variance weighting (the default is TRUE). If set to FALSE, unweighted averages are computed.
-
checkpd
+
checkpd
logical to specify whether to check that the variance-covariance matrices of the sampling errors within clusters are positive definite (the default is TRUE).
-
fun
+
fun
optional list with three functions for aggregating other variables besides the effect sizes or outcomes within clusters (for numeric/integer variables, for logicals, and for all other types, respectively).
-
na.rm
+
na.rm
logical to specify whether NA values should be removed before aggregating values within clusters (the default is TRUE). Can also be a vector with two logicals (the first pertaining to the effect sizes or outcomes, the second to all other variables).
-
addk
+
addk
logical to specify whether to add the cluster size as a new variable (called ki) to the dataset (the default is FALSE).
-
subset
+
subset
optional (logical or numeric) vector to specify the subset of rows to include when aggregating the effect sizes or outcomes.
-
select
+
select
optional vector to specify the names of the variables to include in the aggregated dataset.
-
digits
+
digits
optional integer to specify the number of decimal places to which the printed results should be rounded (the default is to take the value from the object).
-
var.names
+
var.names
optional character vector with two elements to specify the name of the variable that contains the observed effect sizes or outcomes and the name of the variable with the corresponding sampling variances (when unspecified, the function attempts to set these automatically based on the object).
-
...
+
...
other arguments.
@@ -175,11 +176,7 @@
Details
Value
-
-
-
An object of class c("escalc","data.frame") that contains the (selected) variables aggregated to the cluster level.
-
-
+
An object of class c("escalc","data.frame") that contains the (selected) variables aggregated to the cluster level.
The object is formatted and printed with the print function.
Likelihood Ratio and Wald-Type Tests for 'rma' Objects
-
+
anova.rma.Rd
@@ -95,43 +95,44 @@
Likelihood Ratio and Wald-Type Tests for 'rma' Objects
-
# S3 method for rma
+
# S3 method for class 'rma'anova(object, object2, btt, X, att, Z, rhs, adjust, digits, refit=FALSE, ...)
Arguments
-
object
+
+
object
an object of class "rma.uni" or "rma.mv".
-
object2
+
object2
an (optional) object of class "rma.uni" or "rma.mv". Only relevant when conducting a model comparison and likelihood ratio test. See ‘Details’.
-
btt
+
btt
optional vector of indices (or list thereof) to specify which coefficients should be included in the Wald-type test. Can also be a string to grep for. See ‘Details’.
-
X
+
X
optional numeric vector or matrix to specify one or more linear combinations of the coefficients in the model that should be tested. See ‘Details’.
-
att
+
att
optional vector of indices (or list thereof) to specify which scale coefficients should be included in the Wald-type test. Can also be a string to grep for. See ‘Details’. Only relevant for location-scale models (see rma.uni).
-
Z
+
Z
optional numeric vector or matrix to specify one or more linear combinations of the scale coefficients in the model that should be tested. See ‘Details’. Only relevant for location-scale models (see rma.uni).
-
rhs
+
rhs
optional scalar or vector of values for the right-hand side of the null hypothesis when testing a set of coefficients (via btt or att) or linear combinations thereof (via X or Z). If unspecified, this defaults to a vector of zeros of the appropriate length. See ‘Details’.
-
adjust
+
adjust
optional argument to specify (as a character string) a method for adjusting the p-values of Wald-type tests for multiple testing. See p.adjust for possible options. Can be abbreviated. Can also be a logical and if TRUE, then a Bonferroni correction is used.
-
digits
+
digits
optional integer to specify the number of decimal places to which the printed results should be rounded. If unspecified, the default is to take the value from the object.
-
refit
+
refit
logical to specify whether models fitted with REML estimation and differing in their fixed effects should be refitted with ML estimation when conducting a likelihood ratio test (the default is FALSE).
-
...
+
...
other arguments.
@@ -150,9 +151,7 @@
Details
Value
-
-
-
An object of class "anova.rma". When a single model is specified (without any further arguments or together with the btt or att argument), the object is a list containing the following components:
+
An object of class "anova.rma". When a single model is specified (without any further arguments or together with the btt or att argument), the object is a list containing the following components:
QM
test statistic of the Wald-type test of the model coefficients.
@@ -178,8 +177,6 @@
Value
some additional elements/values.
When btt or att was a list, then the object is a list of class "list.anova.rma", where each element is an "anova.rma" object as described above.
-
-
When argument X is used, the object is a list containing the following components:
QM
test statistic of the omnibus Wald-type test of all linear combinations.
baujat(x, ...)
-# S3 method for rma
+# S3 method for class 'rma'baujat(x, xlim, ylim, xlab, ylab, cex, symbol="ids", grid=TRUE, progbar=FALSE, ...)
Arguments
-
x
+
+
x
an object of class "rma".
-
xlim
+
xlim
x-axis limits. If unspecified, the function sets the x-axis limits to some sensible values.
-
ylim
+
ylim
y-axis limits. If unspecified, the function sets the y-axis limits to some sensible values.
-
xlab
+
xlab
title for the x-axis. If unspecified, the function sets an appropriate axis title.
-
ylab
+
ylab
title for the y-axis. If unspecified, the function sets an appropriate axis title.
-
cex
+
cex
symbol/character expansion factor.
-
symbol
+
symbol
either an integer to specify the pch value (i.e., plotting symbol), or "slab" to plot the study labels, or "ids" (the default) to plot the study id numbers.
-
grid
+
grid
logical to specify whether a grid should be added to the plot. Can also be a color name.
-
progbar
+
progbar
logical to specify whether a progress bar should be shown (the default is FALSE).
-
...
+
...
other arguments.
@@ -143,9 +144,7 @@
Details
Value
-
-
-
A data frame with components:
+
A data frame with components:
x
the x-axis coordinates of the points that were plotted.
Best Linear Unbiased Predictions for 'rma.uni' Objects
-
+
blup.Rd
@@ -97,36 +97,35 @@
Best Linear Unbiased Predictions for 'rma.uni' Objects
blup(x, ...)
-# S3 method for rma.uni
+# S3 method for class 'rma.uni'blup(x, level, digits, transf, targs, ...)
Arguments
-
x
+
+
x
an object of class "rma.uni".
-
level
+
level
numeric value between 0 and 100 to specify the prediction interval level (see here for details). If unspecified, the default is to take the value from the object.
-
digits
+
digits
optional integer to specify the number of decimal places to which the printed results should be rounded. If unspecified, the default is to take the value from the object.
-
transf
+
transf
optional argument to specify a function to transform the predicted values and interval bounds (e.g., transf=exp; see also transf). If unspecified, no transformation is used.
-
targs
+
targs
optional arguments needed by the function specified under transf.
-
...
+
...
other arguments.
Value
-
-
-
An object of class "list.rma". The object is a list containing the following components:
+
An object of class "list.rma". The object is a list containing the following components:
# S3 method for class 'rma.uni'confint(object, parm, level, fixed=FALSE, random=TRUE, type,digits, transf, targs, verbose=FALSE, control, ...)
-# S3 method for rma.mh
+# S3 method for class 'rma.mh'confint(object, parm, level, digits, transf, targs, ...)
-# S3 method for rma.peto
+# S3 method for class 'rma.peto'confint(object, parm, level, digits, transf, targs, ...)
-# S3 method for rma.glmm
+# S3 method for class 'rma.glmm'confint(object, parm, level, digits, transf, targs, ...)
-# S3 method for rma.mv
+# S3 method for class 'rma.mv'confint(object, parm, level, fixed=FALSE, sigma2, tau2, rho, gamma2, phi,digits, transf, targs, verbose=FALSE, control, ...)
-# S3 method for rma.uni.selmodel
+# S3 method for class 'rma.uni.selmodel'confint(object, parm, level, fixed=FALSE, tau2, delta,digits, transf, targs, verbose=FALSE, control, ...)
-# S3 method for rma.ls
+# S3 method for class 'rma.ls'confint(object, parm, level, fixed=FALSE, alpha,digits, transf, targs, verbose=FALSE, control, ...)
Arguments
-
object
+
+
object
an object of class "rma.uni", "rma.mh", "rma.peto", "rma.mv", "rma.uni.selmodel", or "rma.ls". The method is not yet implemented for objects of class "rma.glmm".
-
parm
+
parm
this argument is here for compatibility with the generic function confint, but is (currently) ignored.
-
fixed
+
fixed
logical to specify whether confidence intervals for the model coefficients should be returned.
-
random
+
random
logical to specify whether a confidence interval for the amount of (residual) heterogeneity should be returned.
-
type
+
type
optional character string to specify the method for computing the confidence interval for the amount of (residual) heterogeneity (either "QP", "GENQ", "PL", or "HT").
-
sigma2
+
sigma2
integer to specify for which \(\sigma^2\) parameter a confidence interval should be obtained.
-
tau2
+
tau2
integer to specify for which \(\tau^2\) parameter a confidence interval should be obtained.
-
rho
+
rho
integer to specify for which \(\rho\) parameter the confidence interval should be obtained.
-
gamma2
+
gamma2
integer to specify for which \(\gamma^2\) parameter a confidence interval should be obtained.
-
phi
+
phi
integer to specify for which \(\phi\) parameter a confidence interval should be obtained.
-
delta
+
delta
integer to specify for which \(\delta\) parameter a confidence interval should be obtained.
-
alpha
+
alpha
integer to specify for which \(\alpha\) parameter a confidence interval should be obtained.
-
level
+
level
numeric value between 0 and 100 to specify the confidence interval level (see here for details). If unspecified, the default is to take the value from the object.
-
digits
+
digits
optional integer to specify the number of decimal places to which the results should be rounded. If unspecified, the default is to take the value from the object.
-
transf
+
transf
optional argument to specify a function to transform the model coefficients and interval bounds (e.g., transf=exp; see also transf). If unspecified, no transformation is used.
-
targs
+
targs
optional arguments needed by the function specified under transf.
-
verbose
+
verbose
logical to specify whether output should be generated on the progress of the iterative algorithms used to obtain the confidence intervals (the default is FALSE). See ‘Details’.
-
control
+
control
list of control values for the iterative algorithms. If unspecified, default values are used. See ‘Note’.
-
...
+
...
other arguments.
@@ -195,9 +196,7 @@
Details
Value
-
-
-
An object of class "confint.rma". The object is a list with either one or two elements (named fixed and random) with the following elements:
+
An object of class "confint.rma". The object is a list with either one or two elements (named fixed and random) with the following elements:
estimate
estimate of the model coefficient, variance/correlation component, or selection model parameter.
@@ -209,8 +208,6 @@
Value
When obtaining confidence intervals for multiple components, the object is a list of class "list.confint.rma", where each element is a "confint.rma" object as described above.
-
-
The results are formatted and printed with the print function. To format the results as a data frame, one can use the as.data.frame function.
Construct Contrast Matrix for Two-Group Comparisons
-
+
contrmat.Rd
@@ -100,28 +100,29 @@
Construct Contrast Matrix for Two-Group Comparisons
Arguments
-
data
+
+
data
a data frame in wide format.
-
grp1
+
grp1
either the name (given as a character string) or the position (given as a single number) of the first group variable in the data frame.
-
grp2
+
grp2
either the name (given as a character string) or the position (given as a single number) of the second group variable in the data frame.
-
last
+
last
optional character string to specify which group will be placed in the last column of the matrix (must be one of the groups in the group variables). If not given, the most frequently occurring second group is placed last.
-
shorten
+
shorten
logical to specify whether the variable names corresponding to the group names should be shortened (the default is FALSE).
-
minlen
+
minlen
integer to specify the minimum length of the shortened variable names (the default is 2).
-
check
+
check
logical to specify whether the variables names should be checked to ensure that they are syntactically valid variable names and if not, they are adjusted (by make.names) so that they are (the default is TRUE).
-
append
+
append
logical to specify whether the contrast matrix should be appended to the data frame specified via the data argument (the default is TRUE). If append=FALSE, only the contrast matrix is returned.
@@ -134,9 +135,7 @@
Details
Value
-
-
-
A matrix with as many variables as there are groups.
+
A matrix with as many variables as there are groups.
Reconstruct Cell Frequencies of \(2 \times 2\) Tables
-
+
conv.2x2.Rd
@@ -101,40 +101,41 @@
Reconstruct Cell Frequencies of \(2 \times 2\) Tables
Arguments
-
ori
+
+
ori
optional vector with the odds ratios corresponding to the tables.
-
ri
+
ri
optional vector with the phi coefficients corresponding to the tables.
-
x2i
+
x2i
optional vector with the (signed) chi-square statistics corresponding to the tables.
-
ni
+
ni
vector with the total sample sizes.
-
n1i
+
n1i
vector with the marginal counts for the outcome of interest on the first variable.
-
n2i
+
n2i
vector with the marginal counts for the outcome of interest on the second variable.
-
correct
+
correct
optional logical (or vector thereof) to specify whether chi-square statistics were computed using Yates's correction for continuity (the default is TRUE).
-
data
+
data
optional data frame containing the variables given to the arguments above.
-
include
+
include
optional (logical or numeric) vector to specify the subset of studies for which the cell frequencies should be reconstructed.
-
var.names
+
var.names
character vector with four elements to specify the names of the variables for the reconstructed cell frequencies (the default is c("ai","bi","ci","di")).
-
append
+
append
logical to specify whether the data frame provided via the data argument should be returned together with the reconstructed values (the default is TRUE).
-
replace
+
replace
character string or logical to specify how values in var.names should be replaced (only relevant when using the data argument and if variables in var.names already exist in the data frame). See the ‘Value’ section for more details.
@@ -154,14 +155,8 @@
Details
Value
-
-
-
If the data argument was not specified or append=FALSE, a data frame with four variables called var.names with the reconstructed cell frequencies.
-
-
+
If the data argument was not specified or append=FALSE, a data frame with four variables called var.names with the reconstructed cell frequencies.
If data was specified and append=TRUE, then the original data frame is returned. If var.names[j] (for \(\textrm{j} \in \{1, \ldots, 4\}\)) is a variable in data and replace="ifna" (or replace=FALSE), then only missing values in this variable are replaced with the estimated frequencies (where possible) and otherwise a new variable called var.names[j] is added to the data frame.
-
-
If replace="all" (or replace=TRUE), then all values in var.names[j] where a reconstructed cell frequency can be computed are replaced, even for cases where the value in var.names[j] is not missing.
Transform Observed Effect Sizes or Outcomes and their Sampling Variances using the Delta Method
-
+
conv.delta.Rd
@@ -100,34 +100,35 @@
Transform Observed Effect Sizes or Outcomes and their Sampling Variances usi
Arguments
-
yi
+
+
yi
vector with the observed effect sizes or outcomes.
-
vi
+
vi
vector with the corresponding sampling variances.
-
ni
+
ni
vector with the total sample sizes of the studies.
-
data
+
data
optional data frame containing the variables given to the arguments above.
-
include
+
include
optional (logical or numeric) vector to specify the subset of studies for which the transformation should be carried out.
-
transf
+
transf
a function which should be used for the transformation.
-
var.names
+
var.names
character vector with two elements to specify the name of the variable for the transformed effect sizes or outcomes and the name of the variable for the corresponding sampling variances (if data is an object of class "escalc", the var.names are taken from the object; otherwise the defaults are "yi" and "vi").
-
append
+
append
logical to specify whether the data frame provided via the data argument should be returned together with the estimated values (the default is TRUE).
-
replace
+
replace
character string or logical to specify how values in var.names should be replaced (only relevant when using the data argument and if variables in var.names already exist in the data frame). See the ‘Value’ section for more details.
-
...
+
...
other arguments for the transformation function.
@@ -140,14 +141,8 @@
Details
Value
-
-
-
If the data argument was not specified or append=FALSE, a data frame of class c("escalc","data.frame") with two variables called var.names[1] (by default "yi") and var.names[2] (by default "vi") with the transformed observed effect sizes or outcomes and the corresponding sampling variances (computed as described above).
-
-
+
If the data argument was not specified or append=FALSE, a data frame of class c("escalc","data.frame") with two variables called var.names[1] (by default "yi") and var.names[2] (by default "vi") with the transformed observed effect sizes or outcomes and the corresponding sampling variances (computed as described above).
If data was specified and append=TRUE, then the original data frame is returned. If var.names[1] is a variable in data and replace="ifna" (or replace=FALSE), then only missing values in this variable are replaced with the transformed observed effect sizes or outcomes (where possible) and otherwise a new variable called var.names[1] is added to the data frame. Similarly, if var.names[2] is a variable in data and replace="ifna" (or replace=FALSE), then only missing values in this variable are replaced with the sampling variances calculated as described above (where possible) and otherwise a new variable called var.names[2] is added to the data frame.
-
-
If replace="all" (or replace=TRUE), then all values in var.names[1] and var.names[2] are replaced, even for cases where the value in var.names[1] and var.names[2] is not missing.
Estimate Means and Standard Deviations from Five-Number Summary Values
-
+
conv.fivenum.Rd
@@ -102,52 +102,53 @@
Estimate Means and Standard Deviations from Five-Number Summary Values
Arguments
-
min
+
+
min
vector with the minimum values.
-
q1
+
q1
vector with the lower/first quartile values.
-
median
+
median
vector with the median values.
-
q3
+
q3
vector with the upper/third quartile values.
-
max
+
max
vector with the maximum values.
-
n
+
n
vector with the sample sizes.
-
data
+
data
optional data frame containing the variables given to the arguments above.
-
include
+
include
optional (logical or numeric) vector to specify the subset of studies for which means and standard deviations should be estimated.
-
method
+
method
character string to specify the method to use. Either "default" (same as "luo/wan/shi" which is the current default), "qe", "bc", "mln", or "blue". Can be abbreviated. See ‘Details’.
-
dist
+
dist
character string to specify the assumed distribution for the underlying data (either "norm" for a normal distribution or "lnorm" for a log-normal distribution). Can also be a string vector if different distributions are assumed for different studies. Only relevant when method="default".
-
transf
+
transf
logical to specify whether the estimated means and standard deviations of the log-transformed data should be back-transformed as described by Shi et al. (2020b) (the default is TRUE). Only relevant when dist="lnorm" and when method="default".
-
test
+
test
logical to specify whether a study should be excluded from the estimation if the test for skewness is significant (the default is TRUE, but whether this is applicable depends on the method; see ‘Details’).
-
var.names
+
var.names
character vector with two elements to specify the name of the variable for the estimated means and the name of the variable for the estimated standard deviations (the defaults are "mean" and "sd").
-
append
+
append
logical to specify whether the data frame provided via the data argument should be returned together with the estimated values (the default is TRUE).
-
replace
+
replace
character string or logical to specify how values in var.names should be replaced (only relevant when using the data argument and if variables in var.names already exist in the data frame). See the ‘Value’ section for more details.
Convert Wald-Type Confidence Intervals and Tests to Sampling Variances
-
+
conv.wald.Rd
@@ -101,49 +101,50 @@
Convert Wald-Type Confidence Intervals and Tests to Sampling Variances
Arguments
-
out
+
+
out
vector with the observed effect sizes or outcomes.
-
ci.lb
+
ci.lb
vector with the lower bounds of the corresponding Wald-type CIs.
-
ci.ub
+
ci.ub
vector with the upper bounds of the corresponding Wald-type CIs.
-
zval
+
zval
vector with the Wald-type test statistics.
-
pval
+
pval
vector with the p-values of the Wald-type tests.
-
n
+
n
vector with the total sample sizes of the studies.
-
data
+
data
optional data frame containing the variables given to the arguments above.
-
include
+
include
optional (logical or numeric) vector to specify the subset of studies for which the conversion should be carried out.
-
level
+
level
numeric value (or vector) to specify the confidence interval level(s) (the default is 95; see here for details).
-
transf
+
transf
optional argument to specify a function to transform out, ci.lb, and ci.ub (e.g., transf=log). If unspecified, no transformation is used.
-
check
+
check
logical to specify whether the function should carry out a check to examine if the point estimates fall (approximately) halfway between the CI bounds (the default is TRUE).
-
var.names
+
var.names
character vector with two elements to specify the name of the variable for the observed effect sizes or outcomes and the name of the variable for the corresponding sampling variances (if data is an object of class "escalc", the var.names are taken from the object; otherwise the defaults are "yi" and "vi").
-
append
+
append
logical to specify whether the data frame provided via the data argument should be returned together with the estimated values (the default is TRUE).
-
replace
+
replace
character string or logical to specify how values in var.names should be replaced (only relevant when using the data argument and if variables in var.names already exist in the data frame). See the ‘Value’ section for more details.
-
...
+
...
other arguments.
@@ -194,7 +195,7 @@
Converting Test Statistics and
Similarly, study authors may report the test statistic and/or p-value from a Wald-type test of the form \(\textrm{zval} = y_i / \sqrt{v_i}\) (on the transformed scale if transf is specified), with the corresponding two-sided p-value given by \(\textrm{pval} = 2(1 - \Phi(\textrm{|zval|}))\), where \(\Phi(\cdot)\) denotes the cumulative distribution function of a standard normal distribution (i.e., pnorm). Test statistics and/or corresponding p-values of this form can be supplied via arguments zval and pval.
A given p-value can be back-transformed into the corresponding test statistic (if it is not already available) with \(\textrm{zval} = \Phi^{-1}(1 - \textrm{pval}/2)\), where \(\Phi^{-1}(\cdot)\) denotes the quantile function (i.e., the inverse of the cumulative distribution function) of a standard normal distribution (i.e., qnorm). Then \[v_i = \left(\frac{y_i}{\textrm{zval}}\right)^2\] is used to back-calculate a missing vi value in the dataset.
-
Note that the conversion of a p-value to the corresponding test statistic (which is then converted into sampling variance) as shown above assumes that the exact p-value is reported. If authors only report that the p-value fell below a certain threshold (e.g., \(p < .01\) or if authors only state that the test was significant -- which typically implies \(p < .05\)), then a common approach is to use the value of the cutoff reported (e.g., if \(p < .01\) is reported, then assume \(p = .01\)), which is conservative (since the actual p-value was below that assumed value by some unknown amount). The conversion will therefore tend to be much less accurate.
+
Note that the conversion of a p-value to the corresponding test statistic (which is then converted into sampling variance) as shown above assumes that the exact p-value is reported. If authors only report that the p-value fell below a certain threshold (e.g., \(p < .01\) or if authors only state that the test was significant – which typically implies \(p < .05\)), then a common approach is to use the value of the cutoff reported (e.g., if \(p < .01\) is reported, then assume \(p = .01\)), which is conservative (since the actual p-value was below that assumed value by some unknown amount). The conversion will therefore tend to be much less accurate.
Using the earlier example, suppose that only the odds ratio and the corresponding two-sided p-value from a Wald-type test (whether the log odds ratio differs significantly from zero) is reported for study 2.
dat <- data.frame(study = 1:3,
@@ -227,14 +228,8 @@
Converting Test Statistics and
Value
-
-
-
If the data argument was not specified or append=FALSE, a data frame of class c("escalc","data.frame") with two variables called var.names[1] (by default "yi") and var.names[2] (by default "vi") with the (transformed) observed effect sizes or outcomes and the corresponding sampling variances (computed as described above).
-
-
+
If the data argument was not specified or append=FALSE, a data frame of class c("escalc","data.frame") with two variables called var.names[1] (by default "yi") and var.names[2] (by default "vi") with the (transformed) observed effect sizes or outcomes and the corresponding sampling variances (computed as described above).
If data was specified and append=TRUE, then the original data frame is returned. If var.names[1] is a variable in data and replace="ifna" (or replace=FALSE), then only missing values in this variable are replaced with the (possibly transformed) observed effect sizes or outcomes from out (where possible) and otherwise a new variable called var.names[1] is added to the data frame. Similarly, if var.names[2] is a variable in data and replace="ifna" (or replace=FALSE), then only missing values in this variable are replaced with the sampling variances back-calculated as described above (where possible) and otherwise a new variable called var.names[2] is added to the data frame.
-
-
If replace="all" (or replace=TRUE), then all values in var.names[1] and var.names[2] are replaced, even for cases where the value in var.names[1] and var.names[2] is not missing.
+# S3 method for class 'rma.uni'
+cumul(x, order, digits, transf, targs, collapse=FALSE, progbar=FALSE, ...)
+# S3 method for class 'rma.mh'
+cumul(x, order, digits, transf, targs, collapse=FALSE, progbar=FALSE, ...)
+# S3 method for class 'rma.peto'
+cumul(x, order, digits, transf, targs, collapse=FALSE, progbar=FALSE, ...)
Arguments
-
x
+
+
x
an object of class "rma.uni", "rma.mh", or "rma.peto".
-
order
+
order
optional argument to specify a variable based on which the studies will be ordered for the cumulative meta-analysis.
-
digits
+
digits
optional integer to specify the number of decimal places to which the printed results should be rounded. If unspecified, the default is to take the value from the object.
-
transf
+
transf
optional argument to specify a function to transform the model coefficients and interval bounds (e.g., transf=exp; see also transf). If unspecified, no transformation is used.
-
targs
+
targs
optional arguments needed by the function specified under transf.
-
progbar
+
collapse
+
logical to specify whether studies with the same value of the order variable should be added simultaneously (the default is FALSE).
+
+
progbar
logical to specify whether a progress bar should be shown (the default is FALSE).
-
...
+
...
other arguments.
@@ -133,14 +137,16 @@
Arguments
Details
For "rma.uni" objects, the model specified via x must be a model without moderators (i.e., either an equal- or a random-effects model).
If argument order is not specified, the studies are added according to their order in the original dataset.
-
When a variable is specified for order, the variable is assumed to be of the same length as the original dataset that was used in the model fitting (and if the data argument was used in the original model fit, then the variable will be searched for within this data frame first). Any subsetting and removal of studies with missing values that was applied during the model fitting is also automatically applied to the variable specified via the order argument. See ‘Examples’.
+
When a variable is specified for order, the variable is assumed to be of the same length as the original dataset that was used in the model fitting (and if the data argument was used in the original model fit, then the variable will be searched for within this data frame first). Any subsetting and removal of studies with missing values that was applied during the model fitting is also automatically applied to the variable specified via the order argument.
+
By default, studies are added one at a time. However, if a variable is specified for the order argument and collapse=TRUE, then studies with the same value of the order variable are added simultaneously.
Value
-
+
An object of class c("list.rma","cumul.rma"). The object is a list containing the following components:
+
k
+
number of studies included in the analysis.
-
An object of class c("list.rma","cumul.rma"). The object is a list containing the following components:
-
estimate
+
estimate
estimated (average) outcomes.
se
@@ -178,8 +184,6 @@
Value
When the model was fitted with test="t", test="knha", test="hksj", or test="adhoc", then zval is called tval in the object that is returned by the function.
-
-
The object is formatted and printed with the print function. To format the results as a data frame, one can use the as.data.frame function. A forest plot showing the results from the cumulative meta-analysis can be obtained with forest. Alternatively, plot can also be used to visualize the results.
a character string to specify which effect size or outcome measure should be calculated. See ‘Details’ for possible options and how the data needed to compute the selected effect size or outcome measure should then be specified (i.e., which of the following arguments need to be used).
-
ai
+
ai
vector with the \(2 \times 2\) table frequencies (upper left cell).
-
bi
+
bi
vector with the \(2 \times 2\) table frequencies (upper right cell).
-
ci
+
ci
vector with the \(2 \times 2\) table frequencies (lower left cell).
-
di
+
di
vector with the \(2 \times 2\) table frequencies (lower right cell).
-
n1i
+
n1i
vector with the group sizes or row totals (first group/row).
-
n2i
+
n2i
vector with the group sizes or row totals (second group/row).
-
x1i
+
x1i
vector with the number of events (first group).
-
x2i
+
x2i
vector with the number of events (second group).
-
t1i
+
t1i
vector with the total person-times (first group).
-
t2i
+
t2i
vector with the total person-times (second group).
-
m1i
+
m1i
vector with the means (first group or time point).
-
m2i
+
m2i
vector with the means (second group or time point).
-
sd1i
+
sd1i
vector with the standard deviations (first group or time point).
-
sd2i
+
sd2i
vector with the standard deviations (second group or time point).
-
xi
+
xi
vector with the frequencies of the event of interest.
-
mi
+
mi
vector with the frequencies of the complement of the event of interest or the group means.
-
ri
+
ri
vector with the raw correlation coefficients.
-
ti
+
ti
vector with the total person-times or t-test statistics.
-
fi
+
fi
vector with the F-test statistics.
-
pi
+
pi
vector with the (signed) p-values.
-
sdi
+
sdi
vector with the standard deviations.
-
r2i
+
r2i
vector with the \(R^2\) values.
-
ni
+
ni
vector with the sample/group sizes.
-
yi
+
yi
vector with the observed effect sizes or outcomes.
-
vi
+
vi
vector with the corresponding sampling variances.
-
sei
+
sei
vector with the corresponding standard errors.
-
data
+
data
optional data frame containing the variables given to the arguments above.
-
slab
+
slab
optional vector with labels for the studies.
-
subset
+
subset
optional (logical or numeric) vector to specify the subset of studies that will be included in the data frame returned by the function.
-
include
+
include
optional (logical or numeric) vector to specify the subset of studies for which the measure should be calculated. See the ‘Value’ section for more details.
-
add
+
add
a non-negative number to specify the amount to add to zero cells, counts, or frequencies. See ‘Details’.
-
to
+
to
a character string to specify when the values under add should be added (either "all", "only0", "if0all", or "none"). See ‘Details’.
-
drop00
+
drop00
logical to specify whether studies with no cases/events (or only cases) in both groups should be dropped when calculating the observed effect sizes or outcomes. See ‘Details’.
-
vtype
+
vtype
a character string to specify the type of sampling variances to calculate. See ‘Details’.
-
var.names
+
var.names
character vector with two elements to specify the name of the variable for the observed effect sizes or outcomes and the name of the variable for the corresponding sampling variances (the defaults are "yi" and "vi").
-
add.measure
+
add.measure
logical to specify whether a variable should be added to the data frame (with default name "measure") that indicates the type of outcome measure computed. When using this option, var.names can have a third element to change this variable name.
-
append
+
append
logical to specify whether the data frame provided via the data argument should be returned together with the observed effect sizes or outcomes and corresponding sampling variances (the default is TRUE).
-
replace
+
replace
logical to specify whether existing values for yi and vi in the data frame should be replaced. Only relevant when append=TRUE and the data frame already contains the yi and vi variables. If replace=TRUE (the default), all of the existing values will be overwritten. If replace=FALSE, only NA values will be replaced. See the ‘Value’ section for more details.
-
digits
+
digits
optional integer to specify the number of decimal places to which the printed results should be rounded. If unspecified, the default is 4. Note that the values are stored without rounding in the returned object. See also here for further details on how to control the number of digits in the output.
-
...
+
...
other arguments.
@@ -550,9 +551,7 @@
(6) Converting a Data Fram
Value
-
-
-
An object of class c("escalc","data.frame"). The object is a data frame containing the following components:
+
An object of class c("escalc","data.frame"). The object is a data frame containing the following components:
yi
vector with the observed effect sizes or outcomes.
@@ -561,17 +560,9 @@
Value
If a data frame was specified via the data argument and append=TRUE, then variables yi and vi are appended to this data frame. Note that the var.names argument actually specifies the names of these two variables ("yi" and "vi" are the defaults).
-
-
If the data frame already contains two variables with names as specified by the var.names argument, the values for these two variables will be overwritten when replace=TRUE (which is the default). By setting replace=FALSE, only values that are NA will be replaced.
-
-
The subset argument can be used to select the studies that will be included in the data frame returned by the function. On the other hand, the include argument simply selects for which studies the measure will be computed (if it shouldn't be computed for all of them).
-
-
The object is formatted and printed with the print function. The summary function can be used to obtain confidence intervals for the individual outcomes. See methods.escalc for some additional method functions for "escalc" objects.
-
-
With the aggregate function, one can aggregate multiple effect sizes or outcomes belonging to the same study (or some other clustering variable) into a single combined effect size or outcome.
Fit Statistics and Information Criteria for 'rma' Objects
-
+
fitstats.Rd
@@ -97,51 +97,44 @@
Fit Statistics and Information Criteria for 'rma' Objects
fitstats(object, ...)
-# S3 method for rma
+# S3 method for class 'rma'fitstats(object, ..., REML)
-# S3 method for rma
+# S3 method for class 'rma'logLik(object, REML, ...)
-# S3 method for rma
+# S3 method for class 'rma'deviance(object, REML, ...)
-# S3 method for rma
+# S3 method for class 'rma'AIC(object, ..., k=2, correct=FALSE)
-# S3 method for rma
+# S3 method for class 'rma'BIC(object, ...)
Arguments
-
object
+
+
object
an object of class "rma".
-
...
+
...
optionally more fitted model objects (only for fitstats(), AIC(), and BIC()).
-
REML
+
REML
logical to specify whether the regular or restricted likelihood function should be used to obtain the fit statistics and information criteria. Defaults to the method of estimation used (i.e., TRUE if object was fitted with method="REML" and FALSE otherwise).
-
k
+
k
numeric value to specify the penalty per parameter. The default (k=2) is the classical AIC. See AIC for more details.
-
correct
+
correct
logical to specify whether the regular (default) or corrected (i.e., AICc) should be extracted.
Value
-
-
-
For fitstats, a data frame with the (restricted) log-likelihood, deviance, AIC, BIC, and AICc values for each model passed to the function.
-
-
+
For fitstats, a data frame with the (restricted) log-likelihood, deviance, AIC, BIC, and AICc values for each model passed to the function.
For logLik, an object of class "logLik", providing the (restricted) log-likelihood of the model evaluated at the estimated coefficient(s).
-
-
For deviance, a numeric value with the corresponding deviance.
-
-
For AIC and BIC, either a numeric value with the corresponding AIC, AICc, or BIC or a data frame with rows corresponding to the models and columns representing the number of parameters in the model (df) and the AIC, AICc, or BIC.
an object of class "cumul.rma" obtained with cumul.
-
annotate
+
annotate
logical to specify whether annotations should be added to the plot (the default is TRUE).
-
header
+
header
logical to specify whether column headings should be added to the plot (the default is FALSE). Can also be a character vector to specify the left and right headings (or only the left one).
-
xlim
+
xlim
horizontal limits of the plot region. If unspecified, the function sets the horizontal plot limits to some sensible values.
-
alim
+
alim
the x-axis limits. If unspecified, the function sets the x-axis limits to some sensible values.
-
olim
+
olim
optional argument to specify observation/outcome limits. If unspecified, no limits are used.
-
ylim
+
ylim
the y-axis limits of the plot. If unspecified, the function sets the y-axis limits to some sensible values. Can also be a single value to set the lower bound (while the upper bound is still set automatically).
-
at
+
at
position of the x-axis tick marks and corresponding labels. If unspecified, the function sets the tick mark positions/labels to some sensible values.
-
steps
+
steps
the number of tick marks for the x-axis (the default is 5). Ignored when the positions are specified via the at argument.
-
level
-
numeric value between 0 and 100 to specify the confidence interval level (see here for details). The default is to take the value from the object.
-
-
refline
+
refline
numeric value to specify the location of the vertical ‘reference’ line (the default is 0). The line can be suppressed by setting this argument to NA. Can also be a vector to add multiple lines.
-
digits
+
digits
integer to specify the number of decimal places to which the tick mark labels of the x-axis and the annotations should be rounded (the default is 2L). Can also be a vector of two integers, the first to specify the number of decimal places for the annotations, the second for the x-axis labels. When specifying an integer (e.g., 2L), trailing zeros after the decimal mark are dropped for the x-axis labels. When specifying a numeric value (e.g., 2), trailing zeros are retained.
-
width
+
width
optional integer to manually adjust the width of the columns for the annotations (either a single integer or a vector of the same length as the number of annotation columns).
-
xlab
+
xlab
title for the x-axis. If unspecified, the function sets an appropriate axis title. Can also be a vector of three/two values (to also/only add labels at the end points of the x-axis limits).
-
ilab
+
ilab
optional vector, matrix, or data frame providing additional information about the studies that should be added to the plot.
-
ilab.lab
+
ilab.lab
optional character vector with (column) labels for the variable(s) given via ilab.
-
ilab.xpos
+
ilab.xpos
optional numeric vector to specify the horizontal position(s) of the variable(s) given via ilab.
-
ilab.pos
+
ilab.pos
integer(s) (either 1, 2, 3, or 4) to specify the alignment of the variable(s) given via ilab (2 means right, 4 means left aligned). If unspecified, the default is to center the values.
-
transf
+
transf
optional argument to specify a function to transform the estimates and confidence interval bounds (e.g., transf=exp; see also transf). If unspecified, no transformation is used.
-
atransf
+
atransf
optional argument to specify a function to transform the x-axis labels and annotations (e.g., atransf=exp; see also transf). If unspecified, no transformation is used.
-
targs
+
targs
optional arguments needed by the function specified via transf or atransf.
-
rows
+
rows
optional vector to specify the rows (or more generally, the horizontal positions) for plotting the outcomes. Can also be a single value to specify the row (horizontal position) of the first outcome (the remaining outcomes are then plotted below this starting row).
-
efac
+
efac
vertical expansion factor for confidence interval limits and arrows. The default value of 1 should usually work okay. Can also be a vector of two numbers, the first for CI limits, the second for arrows.
-
pch
+
pch
plotting symbol to use for the estimates. By default, a filled square is used. See points for other options. Can also be a vector of values.
-
psize
+
psize
numeric value to specify the point sizes for the estimates (the default is 1). Can also be a vector of values.
-
col
+
col
optional character string to specify the color of the estimates. Can also be a vector.
-
shade
+
shade
optional character string or a (logical or numeric) vector for shading rows of the plot.
-
colshade
+
colshade
optional argument to specify the color for the shading.
-
lty
+
lty
optional character string to specify the line type for the confidence intervals. If unspecified, the function sets this to "solid" by default.
-
fonts
+
fonts
optional character string to specify the font for the study labels, annotations, and the extra information (if specified via ilab). If unspecified, the default font is used.
-
cex
+
cex
optional character and symbol expansion factor. If unspecified, the function sets this to a sensible value.
-
cex.lab
+
cex.lab
optional expansion factor for the x-axis title. If unspecified, the function sets this to a sensible value.
-
cex.axis
+
cex.axis
optional expansion factor for the x-axis labels. If unspecified, the function sets this to a sensible value.
vector of length \(k\) with the observed effect sizes or outcomes.
-
vi
+
vi
vector of length \(k\) with the corresponding sampling variances.
-
sei
+
sei
vector of length \(k\) with the corresponding standard errors (note: only one of the two, vi or sei, needs to be specified).
-
ci.lb
+
ci.lb
vector of length \(k\) with the corresponding lower confidence interval bounds. Not needed if vi or sei is specified. See ‘Details’.
-
ci.ub
+
ci.ub
vector of length \(k\) with the corresponding upper confidence interval bounds. Not needed if vi or sei is specified. See ‘Details’.
-
annotate
+
annotate
logical to specify whether annotations should be added to the plot (the default is TRUE).
-
showweights
+
showweights
logical to specify whether the annotations should also include the inverse variance weights (the default is FALSE).
-
header
+
header
logical to specify whether column headings should be added to the plot (the default is FALSE). Can also be a character vector to specify the left and right headings (or only the left one).
-
xlim
+
xlim
horizontal limits of the plot region. If unspecified, the function sets the horizontal plot limits to some sensible values.
-
alim
+
alim
the x-axis limits. If unspecified, the function sets the x-axis limits to some sensible values.
-
olim
+
olim
optional argument to specify observation/outcome limits. If unspecified, no limits are used.
-
ylim
+
ylim
the y-axis limits of the plot. If unspecified, the function sets the y-axis limits to some sensible values. Can also be a single value to set the lower bound (while the upper bound is still set automatically).
-
at
+
at
position of the x-axis tick marks and corresponding labels. If unspecified, the function sets the tick mark positions/labels to some sensible values.
-
steps
+
steps
the number of tick marks for the x-axis (the default is 5). Ignored when the positions are specified via the at argument.
-
level
+
level
numeric value between 0 and 100 to specify the confidence interval level (the default is 95; see here for details).
-
refline
+
refline
numeric value to specify the location of the vertical ‘reference’ line (the default is 0). The line can be suppressed by setting this argument to NA. Can also be a vector to add multiple lines.
-
digits
+
digits
integer to specify the number of decimal places to which the tick mark labels of the x-axis and the annotations should be rounded (the default is 2L). Can also be a vector of two integers, the first to specify the number of decimal places for the annotations, the second for the x-axis labels (when showweights=TRUE, can also specify a third value for the weights). When specifying an integer (e.g., 2L), trailing zeros after the decimal mark are dropped for the x-axis labels. When specifying a numeric value (e.g., 2), trailing zeros are retained.
-
width
+
width
optional integer to manually adjust the width of the columns for the annotations (either a single integer or a vector of the same length as the number of annotation columns).
-
xlab
+
xlab
title for the x-axis. If unspecified, the function sets an appropriate axis title. Can also be a vector of three/two values (to also/only add labels at the end points of the x-axis limits).
-
slab
+
slab
optional vector with labels for the \(k\) studies. If unspecified, the function tries to extract study labels from x and otherwise simple labels are created within the function. To suppress labels, set this argument to NA.
-
ilab
+
ilab
optional vector, matrix, or data frame providing additional information about the studies that should be added to the plot.
-
ilab.lab
+
ilab.lab
optional character vector with (column) labels for the variable(s) given via ilab.
-
ilab.xpos
+
ilab.xpos
optional numeric vector to specify the horizontal position(s) of the variable(s) given via ilab.
-
ilab.pos
+
ilab.pos
integer(s) (either 1, 2, 3, or 4) to specify the alignment of the variable(s) given via ilab (2 means right, 4 means left aligned). If unspecified, the default is to center the values.
-
order
+
order
optional character string to specify how the studies should be ordered. Can also be a variable based on which the studies will be ordered. See ‘Details’.
-
subset
+
subset
optional (logical or numeric) vector to specify the subset of studies that should be included in the plot.
-
transf
+
transf
optional argument to specify a function to transform the observed outcomes and corresponding confidence interval bounds (e.g., transf=exp; see also transf). If unspecified, no transformation is used.
-
atransf
+
atransf
optional argument to specify a function to transform the x-axis labels and annotations (e.g., atransf=exp; see also transf). If unspecified, no transformation is used.
-
targs
+
targs
optional arguments needed by the function specified via transf or atransf.
-
rows
+
rows
optional vector to specify the rows (or more generally, the horizontal positions) for plotting the outcomes. Can also be a single value to specify the row (horizontal position) of the first outcome (the remaining outcomes are then plotted below this starting row).
-
efac
+
efac
vertical expansion factor for confidence interval limits and arrows. The default value of 1 should usually work okay. Can also be a vector of two numbers, the first for CI limits, the second for arrows.
-
pch
+
pch
plotting symbol to use for the observed outcomes. By default, a filled square is used. See points for other options. Can also be a vector of values.
-
psize
+
psize
optional numeric value to specify the point sizes for the observed outcomes. If unspecified, the point sizes are a function of the precision of the estimates. Can also be a vector of values.
-
plim
+
plim
numeric vector of length 2 to scale the point sizes (ignored when psize is specified). See ‘Details’.
-
col
+
col
optional character string to specify the color of the observed outcomes. Can also be a vector.
-
shade
+
shade
optional character string or a (logical or numeric) vector for shading rows of the plot. See ‘Details’.
-
colshade
+
colshade
optional argument to specify the color for the shading.
-
lty
+
lty
optional character string to specify the line type for the confidence intervals. If unspecified, the function sets this to "solid" by default.
-
fonts
+
fonts
optional character string to specify the font for the study labels, annotations, and the extra information (if specified via ilab). If unspecified, the default font is used.
-
cex
+
cex
optional character and symbol expansion factor. If unspecified, the function sets this to a sensible value.
-
cex.lab
+
cex.lab
optional expansion factor for the x-axis title. If unspecified, the function sets this to a sensible value.
-
cex.axis
+
cex.axis
optional expansion factor for the x-axis labels. If unspecified, the function sets this to a sensible value.
-
...
+
...
other arguments.
@@ -276,7 +277,7 @@
Additional Optional Arguments
rowadj
numeric vector of length 3 to vertically adjust the position of the study labels, the annotations, and the extra information (if specified via ilab). This is useful for fine-tuning the position of text added with different positional alignments (i.e., argument pos in the text function).
# S3 method for class 'rma'forest(x, annotate=TRUE, addfit=TRUE, addpred=FALSE, showweights=FALSE, header=FALSE,xlim, alim, olim, ylim, at, steps=5,
@@ -108,133 +108,134 @@
Forest Plots (Method for 'rma' Objects)
Arguments
-
x
+
+
x
an object of class "rma".
-
annotate
+
annotate
logical to specify whether annotations should be added to the plot (the default is TRUE).
-
addfit
+
addfit
logical to specify whether the summary estimate (for models without moderators) or fitted values (for models with moderators) should be added to the plot (the default is TRUE). See ‘Details’.
-
addpred
+
addpred
logical to specify whether the bounds of the prediction interval should be added to the plot (the default is FALSE). See ‘Details’.
-
showweights
+
showweights
logical to specify whether the annotations should also include the weights given to the observed outcomes during the model fitting (the default is FALSE). See ‘Details’.
-
header
+
header
logical to specify whether column headings should be added to the plot (the default is FALSE). Can also be a character vector to specify the left and right headings (or only the left one).
-
xlim
+
xlim
horizontal limits of the plot region. If unspecified, the function sets the horizontal plot limits to some sensible values.
-
alim
+
alim
the x-axis limits. If unspecified, the function sets the x-axis limits to some sensible values.
-
olim
+
olim
optional argument to specify observation/outcome limits. If unspecified, no limits are used.
-
ylim
+
ylim
the y-axis limits of the plot. If unspecified, the function sets the y-axis limits to some sensible values. Can also be a single value to set the lower bound (while the upper bound is still set automatically).
-
at
+
at
position of the x-axis tick marks and corresponding labels. If unspecified, the function sets the tick mark positions/labels to some sensible values.
-
steps
+
steps
the number of tick marks for the x-axis (the default is 5). Ignored when the positions are specified via the at argument.
-
level
+
level
numeric value between 0 and 100 to specify the confidence interval level (see here for details). The default is to take the value from the object.
-
refline
+
refline
numeric value to specify the location of the vertical ‘reference’ line (the default is 0). The line can be suppressed by setting this argument to NA. Can also be a vector to add multiple lines.
-
digits
+
digits
integer to specify the number of decimal places to which the tick mark labels of the x-axis and the annotations should be rounded (the default is 2L). Can also be a vector of two integers, the first to specify the number of decimal places for the annotations, the second for the x-axis labels (when showweights=TRUE, can also specify a third value for the weights). When specifying an integer (e.g., 2L), trailing zeros after the decimal mark are dropped for the x-axis labels. When specifying a numeric value (e.g., 2), trailing zeros are retained.
-
width
+
width
optional integer to manually adjust the width of the columns for the annotations (either a single integer or a vector of the same length as the number of annotation columns).
-
xlab
+
xlab
title for the x-axis. If unspecified, the function sets an appropriate axis title. Can also be a vector of three/two values (to also/only add labels at the end points of the x-axis limits).
-
slab
+
slab
optional vector with labels for the \(k\) studies. If unspecified, the function tries to extract study labels from x or simple labels are created within the function. To suppress labels, set this argument to NA.
-
mlab
+
mlab
optional character string giving a label to the summary estimate from an equal- or a random-effects model. If unspecified, the label is created within the function.
-
ilab
+
ilab
optional vector, matrix, or data frame providing additional information about the studies that should be added to the plot.
-
ilab.lab
+
ilab.lab
optional character vector with (column) labels for the variable(s) given via ilab.
-
ilab.xpos
+
ilab.xpos
optional numeric vector to specify the horizontal position(s) of the variable(s) given via ilab.
-
ilab.pos
+
ilab.pos
integer(s) (either 1, 2, 3, or 4) to specify the alignment of the variable(s) given via ilab (2 means right, 4 means left aligned). If unspecified, the default is to center the values.
-
order
+
order
optional character string to specify how the studies should be ordered. Can also be a variable based on which the studies will be ordered. See ‘Details’.
-
transf
+
transf
optional argument to specify a function to transform the observed outcomes, summary estimates, fitted values, and confidence interval bounds (e.g., transf=exp; see also transf). If unspecified, no transformation is used.
-
atransf
+
atransf
optional argument to specify a function to transform the x-axis labels and annotations (e.g., atransf=exp; see also transf). If unspecified, no transformation is used.
-
targs
+
targs
optional arguments needed by the function specified via transf or atransf.
-
rows
+
rows
optional vector to specify the rows (or more generally, the horizontal positions) for plotting the outcomes. Can also be a single value to specify the row (horizontal position) of the first outcome (the remaining outcomes are then plotted below this starting row).
-
efac
+
efac
vertical expansion factor for confidence interval limits, arrows, and the symbol used to denote summary estimates. The default value of 1 should usually work okay. Can also be a vector of two numbers, the first for CI limits and arrows, the second for summary estimates. Can also be a vector of three numbers, the first for CI limits, the second for arrows, the third for summary estimates.
-
pch
+
pch
plotting symbol to use for the observed outcomes. By default, a filled square is used. See points for other options. Can also be a vector of values.
-
psize
+
psize
optional numeric value to specify the point sizes for the observed outcomes. If unspecified, the point sizes are a function of the model weights. Can also be a vector of values.
-
plim
+
plim
numeric vector of length 2 to scale the point sizes (ignored when psize is specified). See ‘Details’.
-
colout
+
colout
optional character string to specify the color of the observed outcomes. Can also be a vector.
-
col
+
col
optional character string to specify the color of the summary polygon or fitted values.
-
border
+
border
optional character string to specify the border color of the summary polygon or fitted values.
-
shade
+
shade
optional character string or a (logical or numeric) vector for shading rows of the plot. See ‘Details’.
-
colshade
+
colshade
optional argument to specify the color for the shading.
-
lty
+
lty
optional character string to specify the line type for the confidence intervals. If unspecified, the function sets this to "solid" by default.
-
fonts
+
fonts
optional character string to specify the font for the study labels, annotations, and the extra information (if specified via ilab). If unspecified, the default font is used.
-
cex
+
cex
optional character and symbol expansion factor. If unspecified, the function sets this to a sensible value.
-
cex.lab
+
cex.lab
optional expansion factor for the x-axis title. If unspecified, the function sets this to a sensible value.
-
cex.axis
+
cex.axis
optional expansion factor for the x-axis labels. If unspecified, the function sets this to a sensible value.
-
...
+
...
other arguments.
@@ -297,7 +298,7 @@
Additional Optional Arguments
rowadj
numeric vector of length 3 to vertically adjust the position of the study labels, the annotations, and the extra information (if specified via ilab). This is useful for fine-tuning the position of text added with different positional alignments (i.e., argument pos in the text function).
integer to specify the number of decimal places to which the values should be rounded. For fmmt, can be a vector of length 2, to specify the number of digits for the test statistic and the p-value, respectively.
-
pname
+
pname
string to add as a prefix to the p-value (e.g., something like "p-val" or just "p").
-
equal
+
equal
logical to specify whether an equal symbol should be shown before the p-value (when it is larger than the rounding cutoff).
-
sep
+
sep
logical to specify whether a space should be added between pname, the equal/lesser symbol, and the p-value.
-
add0
+
add0
logical to specify whether a 0 should be shown before the decimal point when the p-value is below the rounding cutoff.
-
quote
+
quote
logical to specify whether formatted strings should be quoted when printed.
Arguments specific for fmtx:
-
x
+
+
x
vector of numeric values to be formatted.
-
flag
+
flag
a character string giving a format modifier as defined for formatC.
Arguments specific for fmtt:
-
val
+
+
val
test statistic value to be formatted.
-
tname
+
tname
character string for the name of the test statistic.
-
df
+
df
optional value for the degrees of freedom of the test statistic.
-
df1
+
df1
optional value for the numerator degrees of freedom of the test statistic.
-
df2
+
df2
optional value for the denominator degrees of freedom of the test statistic.
-
pval
+
pval
the p-value corresponding to the test statistic.
-
format
+
format
either 1 or 2 to denote whether the degrees of freedom should be given before the test statistic (in parentheses) or after the test statistic.
-
call
+
call
logical to specify whether the formatted test result should be returned as a call or not.
-
...
+
...
other arguments.
@@ -172,9 +174,7 @@
Details
Value
-
-
-
A character vector with the formatted values. By default (i.e., when quote=FALSE), formatted strings are not quoted when printed.
+
A character vector with the formatted values. By default (i.e., when quote=FALSE), formatted strings are not quoted when printed.
# S3 method for class 'rma'formula(x, type="mods", ...)
Arguments
-
x
+
+
x
an object of class "rma".
-
type
+
type
the formula which should be returned; either "mods" (default), "yi" (in case argument yi was used to specify a formula), or "scale" (only for location-scale models).
a vector with the observed effect sizes or outcomes or an object of class "rma".
-
vi
+
vi
vector with the corresponding sampling variances (ignored if x is an object of class "rma").
-
sei
+
sei
vector with the corresponding standard errors (note: only one of the two, vi or sei, needs to be specified).
-
subset
+
subset
optional (logical or numeric) vector to specify the subset of studies that should be used for the calculation (ignored if x is an object of class "rma").
-
data
+
data
optional data frame containing the variables given to the arguments above.
-
type
+
type
optional character string to specify the type of method to use for the calculation of the fail-safe N. Possible options are "Rosenthal" (the default when x is a vector with the observed effect sizes or outcomes), "Orwin", "Rosenberg", or "General" (the default when x is an object of class "rma"). Can be abbreviated. See ‘Details’.
-
alpha
+
alpha
target alpha level for the Rosenthal, Rosenberg, and General methods (the default is .05).
-
target
+
target
target average effect size or outcome for the Orwin and General methods.
-
method
+
method
optional character string to specify the model fitting method for type="General" (if unspecified, either "REML" by default or the method that was used in fitting the "rma" model). See rma.uni for options.
-
exact
+
exact
logical to specify whether the general method should be based on exact (but slower) or approximate (but faster) calculations.
-
verbose
+
verbose
logical to specify whether output should be generated on the progress of the calculations for type="General" (the default is FALSE).
-
digits
+
digits
optional integer to specify the number of decimal places to which the printed results should be rounded.
an object of class "rma" or a vector with the observed effect sizes or outcomes.
-
vi
+
vi
vector with the corresponding sampling variances (needed if x is a vector with the observed effect sizes or outcomes).
-
sei
+
sei
vector with the corresponding standard errors (note: only one of the two, vi or sei, needs to be specified).
-
ni
+
ni
vector with the corresponding sample sizes. Only relevant when passing a vector via x.
-
subset
+
subset
optional (logical or numeric) vector to specify the subset of studies that should be included in the plot. Only relevant when passing a vector via x.
-
yaxis
+
yaxis
either "sei", "vi", "seinv", "vinv", "ni", "ninv", "sqrtni", "sqrtninv", "lni", or "wi" to specify what values should be placed on the y-axis. See ‘Details’.
-
xlim
+
xlim
x-axis limits. If unspecified, the function sets the x-axis limits to some sensible values.
-
ylim
+
ylim
y-axis limits. If unspecified, the function sets the y-axis limits to some sensible values.
-
xlab
+
xlab
title for the x-axis. If unspecified, the function sets an appropriate axis title.
-
ylab
+
ylab
title for the y-axis. If unspecified, the function sets an appropriate axis title.
-
slab
+
slab
optional vector with labels for the \(k\) studies. If unspecified, the function tries to extract study labels from x.
-
steps
+
steps
the number of tick marks for the y-axis (the default is 5).
-
at
+
at
position of the x-axis tick marks and corresponding labels. If unspecified, the function sets the tick mark positions/labels to some sensible values.
-
atransf
+
atransf
optional argument to specify a function to transform the x-axis labels (e.g., atransf=exp; see also transf). If unspecified, no transformation is used.
-
targs
+
targs
optional arguments needed by the function specified via atransf.
-
digits
+
digits
optional integer to specify the number of decimal places to which the tick mark labels of the x- and y-axis should be rounded. Can also be a vector of two integers, the first to specify the number of decimal places for the x-axis, the second for the y-axis labels (e.g., digits=c(2,3)). If unspecified, the function tries to set the argument to some sensible values.
-
level
+
level
numeric value between 0 and 100 to specify the level of the pseudo confidence interval region (see here for details). For "rma" objects, the default is to take the value from the object. May also be a vector of values to obtain multiple regions. See ‘Examples’.
-
addtau2
+
addtau2
logical to specify whether the amount of heterogeneity should be accounted for when drawing the pseudo confidence interval region (the default is FALSE). Ignored when x is a meta-regression model and residuals are plotted. See ‘Details’.
-
type
+
type
either "rstandard" (default) or "rstudent" to specify whether the usual or deleted residuals should be used in creating the funnel plot when x is a meta-regression model. See ‘Details’.
-
back
+
back
optional character string to specify the color of the plotting region background.
-
shade
+
shade
optional character string to specify the color of the pseudo confidence interval region. When level is a vector of values, different shading colors can be specified for each region.
-
hlines
+
hlines
optional character string to specify the color of the horizontal reference lines.
-
refline
+
refline
numeric value to specify the location of the vertical ‘reference’ line and where the pseudo confidence interval should be centered. If unspecified, the reference line is drawn at the equal- or random-effects model estimate and at zero for meta-regression models (in which case the residuals are plotted) or when directly plotting observed outcomes.
-
lty
+
lty
line type for the pseudo confidence interval region and the reference line. The default is to draw dotted lines (see par for other options). Can also be a vector to specify the two line types separately.
-
pch
+
pch
plotting symbol to use for the observed outcomes. By default, a filled circle is used. Can also be a vector of values. See points for other options.
-
pch.fill
+
pch.fill
plotting symbol to use for the outcomes filled in by the trim and fill method. By default, an open circle is used. Only relevant when plotting an object created by the trimfill function.
-
col
+
col
optional character string to specify the (border) color of the points. Can also be a vector.
-
bg
+
bg
optional character string to specify the background color of open plot symbols. Can also be a vector.
-
label
+
label
argument to control the labeling of the points (the default is FALSE). See ‘Details’.
-
offset
+
offset
argument to control the distance between the points and the corresponding labels.
-
legend
+
legend
logical to specify whether a legend should be added to the plot (the default is FALSE). See ‘Details’.
-
...
+
...
other arguments.
@@ -244,9 +245,7 @@
Note
Value
-
-
-
A data frame with components:
+
A data frame with components:
x
the x-axis coordinates of the points that were plotted.
gosh(x, ...)
-# S3 method for rma
+# S3 method for class 'rma'gosh(x, subsets, progbar=TRUE, parallel="no", ncpus=1, cl, ...)
Arguments
-
x
+
+
x
an object of class "rma".
-
subsets
+
subsets
optional integer to specify the number of subsets.
-
progbar
+
progbar
logical to specify whether a progress bar should be shown (the default is TRUE).
-
parallel
+
parallel
character string to specify whether parallel processing should be used (the default is "no"). For parallel processing, set to either "snow" or "multicore". See ‘Note’.
-
ncpus
+
ncpus
integer to specify the number of processes to use in the parallel processing.
-
cl
+
cl
optional cluster to use if parallel="snow". If unspecified, a cluster on the local machine is created for the duration of the call.
-
...
+
...
other arguments.
@@ -136,9 +137,7 @@
Details
Value
-
-
-
An object of class "gosh.rma". The object is a list containing the following components:
+
An object of class "gosh.rma". The object is a list containing the following components:
res
a data frame with the results for each subset (including various heterogeneity statistics and the model coefficient(s)).
Meta-Analysis based on the Method by Henmi and Copas (2010)
-
+
hc.Rd
@@ -97,28 +97,29 @@
Meta-Analysis based on the Method by Henmi and Copas (2010)
hc(object, ...)
-# S3 method for rma.uni
+# S3 method for class 'rma.uni'hc(object, digits, transf, targs, control, ...)
Arguments
-
object
+
+
object
an object of class "rma.uni".
-
digits
+
digits
optional integer to specify the number of decimal places to which the printed results should be rounded. If unspecified, the default is to take the value from the object.
-
transf
+
transf
optional argument to specify a function to transform the estimate and the corresponding interval bounds (e.g., transf=exp; see also transf). If unspecified, no transformation is used.
-
targs
+
targs
optional arguments needed by the function specified under transf.
-
control
+
control
list of control values for the iterative algorithm. If unspecified, default values are used. See ‘Note’.
-
...
+
...
other arguments.
@@ -130,9 +131,7 @@
Details
Value
-
-
-
An object of class "hc.rma.uni". The object is a list containing the following components:
+
An object of class "hc.rma.uni". The object is a list containing the following components:
# S3 method for class 'rma.mv'cooks.distance(model, progbar=FALSE, cluster, reestimate=TRUE, parallel="no", ncpus=1, cl, ...)
-# S3 method for rma.mv
+# S3 method for class 'rma.mv'dfbetas(model, progbar=FALSE, cluster, reestimate=TRUE, parallel="no", ncpus=1, cl, ...)
-# S3 method for rma.mv
+# S3 method for class 'rma.mv'hatvalues(model, type="diagonal", ...)
Arguments
-
model
+
+
model
an object of class "rma.mv".
-
progbar
+
progbar
logical to specify whether a progress bar should be shown (the default is FALSE).
-
cluster
+
cluster
optional vector to specify a clustering variable to use for computing the Cook's distances or DFBETAS values. If unspecified, these measures are computed for the individual observed effect sizes or outcomes.
-
reestimate
+
reestimate
logical to specify whether variance/correlation components should be re-estimated after deletion of the \(i\textrm{th}\) case (the default is TRUE).
-
parallel
+
parallel
character string to specify whether parallel processing should be used (the default is "no"). For parallel processing, set to either "snow" or "multicore". See ‘Note’.
-
ncpus
+
ncpus
integer to specify the number of processes to use in the parallel processing.
-
cl
+
cl
optional cluster to use if parallel="snow". If unspecified, a cluster on the local machine is created for the duration of the call.
-
type
+
type
character string to specify whether only the diagonal of the hat matrix ("diagonal") or the entire hat matrix ("matrix") should be returned.
-
...
+
...
other arguments.
@@ -145,9 +146,7 @@
Details
Value
-
-
-
The cooks.distance function returns a vector. The dfbetas function returns a data frame. The hatvalues function returns either a vector with the diagonal elements of the hat matrix or the entire hat matrix.
+
The cooks.distance function returns a vector. The dfbetas function returns a data frame. The hatvalues function returns either a vector with the diagonal elements of the hat matrix or the entire hat matrix.
# S3 method for class 'rma.uni'influence(model, digits, progbar=FALSE, ...)
-# S3 method for infl.rma.uni
+# S3 method for class 'infl.rma.uni'print(x, digits=x$digits, infonly=FALSE, ...)
-# S3 method for rma.uni
+# S3 method for class 'rma.uni'cooks.distance(model, progbar=FALSE, ...)
-# S3 method for rma.uni
+# S3 method for class 'rma.uni'dfbetas(model, progbar=FALSE, ...)
-# S3 method for rma.uni
+# S3 method for class 'rma.uni'hatvalues(model, type="diagonal", ...)
Arguments
-
model
+
+
model
an object of class "rma.uni".
-
x
+
x
an object of class "infl.rma.uni" (for print).
-
digits
+
digits
optional integer to specify the number of decimal places to which the printed results should be rounded. If unspecified, the default is to take the value from the object.
-
progbar
+
progbar
logical to specify whether a progress bar should be shown (the default is FALSE).
-
infonly
+
infonly
logical to specify whether only the influential cases should be printed (the default is FALSE).
-
type
+
type
character string to specify whether only the diagonal of the hat matrix ("diagonal") or the entire hat matrix ("matrix") should be returned.
-
...
+
...
other arguments.
@@ -161,9 +162,7 @@
Details
Value
-
-
-
An object of class "infl.rma.uni", which is a list containing the following components:
+
An object of class "infl.rma.uni", which is a list containing the following components:
inf
an element of class "list.rma" with the externally standardized residuals, DFFITS values, Cook's distances, covariance ratios, leave-one-out \(\tau^2\) estimates, leave-one-out (residual) heterogeneity test statistics, hat values, weights, and an indicator whether a case is influential.
x-axis limits. If unspecified, the function sets the x-axis limits to some sensible values.
-
ylim
+
ylim
y-axis limits. If unspecified, the function sets the y-axis limits to some sensible values.
-
lim
+
lim
axis limits. If specified, this is used for both xlim and ylim.
-
xlab
+
xlab
title for the x-axis. If unspecified, the function sets an appropriate axis title.
-
ylab
+
ylab
title for the y-axis. If unspecified, the function sets an appropriate axis title.
-
flip
+
flip
logical to specify whether the groups to plot on the x- and y-axis should be flipped (the default is FALSE).
-
ci
+
ci
logical to specify whether the confidence interval region should be shown in the plot (the default is FALSE). Can also be a color name.
-
pi
+
pi
logical to specify whether the prediction interval region should be shown in the plot (the default is FALSE). Can also be a color name.
-
grid
+
grid
logical to specify whether a grid should be added to the plot (the default is FALSE). Can also be a color name.
-
legend
+
legend
logical to specify whether a legend should be added to the plot (the default is FALSE). Can also be a keyword to specify the position of the legend (see legend).
-
add
+
add
See the documentation of the escalc function for more details.
-
to
+
to
See the documentation of the escalc function for more details.
-
transf
+
transf
optional argument to specify a function to transform the outcomes (e.g., transf=exp; see also transf). If unspecified, no transformation is used.
-
targs
+
targs
optional arguments needed by the function specified under transf.
-
pch
+
pch
plotting symbol to use for the outcomes. By default, an open circle is used. Can also be a vector of values. See points for other options.
-
psize
+
psize
optional numeric vector to specify the point sizes for the outcomes. If unspecified, the point sizes are a function of the precision of the outcomes. Can also be a vector of values.
-
plim
+
plim
numeric vector of length 2 to scale the point sizes (ignored when psize is specified). See ‘Details’.
-
col
+
col
optional character string to specify the (border) color of the points. Can also be a vector.
-
bg
+
bg
optional character string to specify the background color of open plot symbols. Can also be a vector. Set to NA to make the plotting symbols transparent.
-
lty
+
lty
optional character vector to specify the line type for the diagonal reference line of no effect and the line that indicates the estimated effect based on the fitted model. If unspecified, the function sets this to c("solid","dashed") by default (use "blank" to suppress a line).
-
...
+
...
other arguments.
@@ -184,9 +185,7 @@
Details
Value
-
-
-
A data frame with components:
+
A data frame with components:
x
the x-axis coordinates of the points that were plotted.
leave1out(x, ...)
-# S3 method for rma.uni
+# S3 method for class 'rma.uni'leave1out(x, digits, transf, targs, progbar=FALSE, ...)
-# S3 method for rma.mh
+# S3 method for class 'rma.mh'leave1out(x, digits, transf, targs, progbar=FALSE, ...)
-# S3 method for rma.peto
+# S3 method for class 'rma.peto'leave1out(x, digits, transf, targs, progbar=FALSE, ...)
Arguments
-
x
+
+
x
an object of class "rma.uni", "rma.mh", or "rma.peto".
-
digits
+
digits
optional integer to specify the number of decimal places to which the printed results should be rounded. If unspecified, the default is to take the value from the object.
-
transf
+
transf
optional argument to specify a function to transform the model coefficients and interval bounds (e.g., transf=exp; see also transf). If unspecified, no transformation is used.
-
targs
+
targs
optional arguments needed by the function specified under transf.
-
progbar
+
progbar
logical to specify whether a progress bar should be shown (the default is FALSE).
-
...
+
...
other arguments.
@@ -132,9 +133,7 @@
Details
Value
-
-
-
An object of class "list.rma". The object is a list containing the following components:
+
An object of class "list.rma". The object is a list containing the following components:
estimate
estimated (average) outcomes.
@@ -170,8 +169,6 @@
Value
When the model was fitted with test="t", test="knha", test="hksj", or test="adhoc", then zval is called tval in the object that is returned by the function.
-
-
The object is formatted and printed with the print function. To format the results as a data frame, one can use the as.data.frame function.
a character string to specify for which effect size or outcome measure the likelihoods should be calculated. See ‘Details’ for possible options and how the data should then be specified.
-
yi
+
yi
vector with the observed effect sizes or outcomes.
-
vi
+
vi
vector with the corresponding sampling variances.
-
sei
+
sei
vector to specify the corresponding standard.
-
ai
+
ai
vector to specify the \(2 \times 2\) table frequencies (upper left cell).
-
bi
+
bi
vector to specify the \(2 \times 2\) table frequencies (upper right cell).
-
ci
+
ci
vector to specify the \(2 \times 2\) table frequencies (lower left cell).
-
di
+
di
vector to specify the \(2 \times 2\) table frequencies (lower right cell).
-
n1i
+
n1i
vector to specify the group sizes or row totals (first group/row).
-
n2i
+
n2i
vector to specify the group sizes or row totals (second group/row).
-
data
+
data
optional data frame containing the variables given to the arguments above.
-
subset
+
subset
optional (logical or numeric) vector to specify the subset of studies that should be included in the plot.
-
drop00
+
drop00
logical to specify whether studies with no cases (or only cases) in both groups should be dropped. See ‘Details’.
-
xvals
+
xvals
integer to specify for how many distinct values the likelihood should be evaluated.
-
xlim
+
xlim
x-axis limits. If unspecified, the function sets the x-axis limits to some sensible values.
-
ylim
+
ylim
y-axis limits. If unspecified, the function sets the y-axis limits to some sensible values.
-
xlab
+
xlab
title for the x-axis. If unspecified, the function sets an appropriate axis title.
-
ylab
+
ylab
title for the y-axis. If unspecified, the function sets an appropriate axis title.
-
scale
+
scale
logical to specify whether the likelihood values should be scaled, so that the total area under each curve is (approximately) equal to 1.
-
lty
+
lty
the line types (either a single value or a vector of length \(k\)). If unspecified, the function sets the line types according to some characteristics of the likelihood function. See ‘Details’.
-
lwd
+
lwd
the line widths (either a single value or a vector of length \(k\)). If unspecified, the function sets the widths according to the sampling variances (so that the line is thicker for more precise studies and vice-versa).
-
col
+
col
the line colors (either a single value or a vector of length \(k\)). If unspecified, the function uses various shades of gray according to the sampling variances (so that darker shades are used for more precise studies and vice-versa).
-
level
+
level
numeric value between 0 and 100 to specify the plotting limits for each likelihood line in terms of the confidence interval (the default is 99.99).
-
refline
+
refline
numeric value to specify the location of the vertical ‘reference’ line (the default is 0). The line can be suppressed by setting this argument to NA.
Fit Regression Models based on a Correlation and Covariance Matrix
-
+
matreg.Rd
@@ -101,40 +101,41 @@
Fit Regression Models based on a Correlation and Covariance Matrix
Arguments
-
y
+
+
y
index (or name given as a character string) of the outcome variable.
-
x
+
x
indices (or names given as a character vector) of the predictor variables.
-
R
+
R
correlation or covariance matrix (or only the lower triangular part including the diagonal).
-
n
+
n
sample size based on which the elements in the correlation/covariance matrix were computed.
-
V
+
V
variance-covariance matrix of the lower triangular elements of the correlation/covariance matrix. Either V or n should be specified, not both. See ‘Details’.
-
cov
+
cov
logical to specify whether R is a covariance matrix (the default is FALSE).
-
means
+
means
optional vector to specify the means of the variables (only relevant when cov=TRUE).
-
ztor
+
ztor
logical to specify whether R is a matrix of r-to-z transformed correlations and hence should be back-transformed to raw correlations (the default is FALSE). See ‘Details’.
-
nearpd
+
nearpd
logical to specify whether the nearPD function from the Matrix package should be used when the \(R_{x,x}\) matrix cannot be inverted. See ‘Note’.
-
level
+
level
numeric value between 0 and 100 to specify the confidence interval level (the default is 95; see here for details).
-
digits
+
digits
optional integer to specify the number of decimal places to which the printed results should be rounded.
-
...
+
...
other arguments.
@@ -148,9 +149,7 @@
Details
Value
-
-
-
An object of class "matreg". The object is a list containing the following components:
+
An object of class "matreg". The object is a list containing the following components:
tab
a data frame with the estimated model coefficients, standard errors, test statistics, degrees of freedom (only for t-tests), p-values, and lower/upper confidence interval bounds.
The paper mentioned above is a good starting place for those interested in using the package. The purpose of the article is to provide a general overview of the package and its capabilities (as of version 1.4-0). Not all of the functions and options are described in the paper, but it should provide a useful introduction to the package. The paper can be freely downloaded from the URL given above or can be directly loaded with the command vignette("metafor").
In addition to reading the paper, carefully read this page and then the help pages for the escalc and the rma.uni functions (or the rma.mh, rma.peto, rma.glmm, and/or rma.mv functions if you intend to use these methods). The help pages for these functions provide links to many additional functions, which can be used after fitting a model. You can also read the entire documentation online at https://wviechtb.github.io/metafor/ (where it is nicely formatted and the output from all examples is provided).
-
A (pdf) diagram showing the various functions in the metafor package (and how they are related to each other) can be opened with the command vignette("diagram", package="metafor").
+
A (pdf) diagram showing the various functions in the metafor package (and how they are related to each other) can be opened with the command vignette("diagram", package="metafor").
Finally, additional information about the package, several detailed analysis examples, examples of plots and figures provided by the package (with the corresponding code), some additional tips and notes, and a FAQ can be found on the package website at https://www.metafor-project.org.
# \dontrun{metafor.news()
-#> Changes in version 4.7-23 (2024-07-02)
+#> Changes in version 4.7-24 (2024-07-09)
+#>
+#> - added collapse argument to the various cumul() functions#>#> - the predict.rma() and predict.rma.ls() functions now also accept a#> matrix as input that includes a column for the intercept term (in
@@ -2394,17 +2396,17 @@
# S3 method for class 'confint.rma'as.data.frame(x, ...)
-# S3 method for list.confint.rma
+# S3 method for class 'list.confint.rma'as.data.frame(x, ...)
Arguments
-
x
+
+
x
an object of class "confint.rma" or "list.confint.rma".
# S3 method for escalc
-[(x, i, ...)
-# S3 method for escalc
-$(x, name) <- value
-# S3 method for escalc
-cbind(..., deparse.level=1)
-# S3 method for escalc
-rbind(..., deparse.level=1)
+
# S3 method for class 'escalc'
+x[i, ...]
+# S3 method for class 'escalc'
+x$name<-value
+# S3 method for class 'escalc'
+cbind(..., deparse.level=1)
+# S3 method for class 'escalc'
+rbind(..., deparse.level=1)
# S3 method for list.rma
-as.data.frame(x, ...)
-# S3 method for list.rma
-as.matrix(x, ...)
-# S3 method for list.rma
-[(x, i, ...)
-# S3 method for list.rma
-head(x, n=6L, ...)
-# S3 method for list.rma
-tail(x, n=6L, ...)
-# S3 method for list.rma
-$(x, name) <- value
+
# S3 method for class 'list.rma'
+as.data.frame(x, ...)
+# S3 method for class 'list.rma'
+as.matrix(x, ...)
+# S3 method for class 'list.rma'
+x[i, ...]
+# S3 method for class 'list.rma'
+head(x, n=6L, ...)
+# S3 method for class 'list.rma'
+tail(x, n=6L, ...)
+# S3 method for class 'list.rma'
+x$name<-value
The name of an option. If unspecified, all options are returned.
-
default
+
default
value to return if the option name does not exist.
-
...
+
...
one or more option names and the corresponding values to which they should be set.
@@ -133,13 +134,11 @@
Details
theme
character string to specify how plots created by the package should be themed. The default is "default", which means that the default foreground and background colors of plotting devices are used. Alternative options are "light" and "dark", which forces plots to be drawn with a light or dark background, respectively. See here for further details. RStudio users can also set this to "auto", in which case plotting colors are chosen depending on the RStudio theme used (for some themes, using "auto2" might be aesthetically more pleasing). One can also use setmfopt(theme="custom", fg=<color>, bg=<color>) to set the foreground and background colors to custom choices (depending on the colors chosen, using "custom2" might be aesthetically more pleasing).
-
+
Value
-
-
-
Either a vector with the value for the chosen option or a list with all options.
+
Either a vector with the value for the chosen option or a list with all options.
Construct a Pairwise Contrast Matrix for 'rma' Objects
-
+
pairwise.Rd
@@ -100,32 +100,25 @@
Construct a Pairwise Contrast Matrix for 'rma' Objects
Arguments
-
x
+
+
x
an object of class "rma".
-
btt
+
btt
vector of indices to specify for which coefficients pairwise contrasts should be constructed. Can also be a string to grep for. See ‘Details’.
-
btt2
+
btt2
optional argument to specify a second set of coefficients that should also be included in the contrast matrix.
-
...
+
...
other arguments.
Value
-
-
-
When a meta-regression model includes a categorical moderator variable (i.e., a factor), there is often interest in testing whether the coefficients representing the various levels of the factor differ significantly from each other. The present function constructs the pairwise contrast matrix between all factor levels for a particular factor, which can be used together with the anova function to carry out such tests and the predict function to obtain corresponding confidence intervals.
-
-
+
When a meta-regression model includes a categorical moderator variable (i.e., a factor), there is often interest in testing whether the coefficients representing the various levels of the factor differ significantly from each other. The present function constructs the pairwise contrast matrix between all factor levels for a particular factor, which can be used together with the anova function to carry out such tests and the predict function to obtain corresponding confidence intervals.
The x argument is used to specify a meta-regression model and the btt argument the indices of the coefficients for which pairwise contrasts should be constructed. For example, with btt=2:4, contrasts are formed based on the second, third, and fourth coefficient of the model. Instead of specifying the coefficient numbers, one can specify a string for btt. In that case, grep will be used to search for all coefficient names that match the string.
-
-
At times, it may be useful to include a second set of coefficients in the contrast matrix (not as pairwise contrasts, but as ‘main effects’). This can be done via the btt2 argument.
-
-
When using the present function in a call to the anova or predict functions, argument x does not need to specified, as the function will then automatically construct the contrast matrix based on the model object passed to the anova or predict function. See below for examples.
permutest(x, ...)
-# S3 method for rma.uni
+# S3 method for class 'rma.uni'permutest(x, exact=FALSE, iter=1000, btt=x$btt, permci=FALSE, progbar=TRUE, digits, control, ...)
-# S3 method for rma.ls
+# S3 method for class 'rma.ls'permutest(x, exact=FALSE, iter=1000, btt=x$btt, att=x$att, progbar=TRUE, digits, control, ...)
Arguments
-
x
+
+
x
an object of class "rma.uni" or "rma.ls".
-
exact
+
exact
logical to specify whether an exact permutation test should be carried out (the default is FALSE). See ‘Details’.
-
iter
+
iter
integer to specify the number of iterations for the permutation test when not doing an exact test (the default is 1000).
-
btt
+
btt
optional vector of indices (or list thereof) to specify which coefficients should be included in the Wald-type test. Can also be a string to grep for.
-
att
+
att
optional vector of indices (or list thereof) to specify which scale coefficients should be included in the Wald-type test. Can also be a string to grep for.
-
permci
+
permci
logical to specify whether permutation-based confidence intervals (CIs) should also be constructed (the default is FALSE). Can also be a vector of indices to specify for which coefficients a permutation-based CI should be obtained.
-
progbar
+
progbar
logical to specify whether a progress bar should be shown (the default is TRUE).
-
digits
+
digits
optional integer to specify the number of decimal places to which the printed results should be rounded. If unspecified, the default is to take the value from the object.
-
control
+
control
list of control values for numerical comparisons (comptol) and for uniroot (i.e., tol and maxiter). The latter is only relevant when permci=TRUE. See ‘Note’.
-
...
+
...
other arguments.
@@ -176,9 +177,7 @@
Permutation Tests for Locat
Value
-
-
-
An object of class "permutest.rma.uni". The object is a list containing the following components:
+
An object of class "permutest.rma.uni". The object is a list containing the following components:
an object of class "cumul.rma" obtained with cumul.
-
yaxis
+
yaxis
either "tau2", "I2", or "H2" to specify what values should be placed on the y-axis. See ‘Details’.
-
xlim
+
xlim
x-axis limits. If unspecified, the function sets the x-axis limits to some sensible values.
-
ylim
+
ylim
y-axis limits. If unspecified, the function sets the y-axis limits to some sensible values.
-
xlab
+
xlab
title for the x-axis. If unspecified, the function sets an appropriate axis title.
-
ylab
+
ylab
title for the y-axis. If unspecified, the function sets an appropriate axis title.
-
at
+
at
position of the x-axis tick marks and corresponding labels. If unspecified, the function sets the tick mark positions/labels to some sensible values.
-
transf
+
transf
optional argument to specify a function to transform the summary estimates (e.g., transf=exp; see also transf). If unspecified, no transformation is used.
-
atransf
+
atransf
optional argument to specify a function to transform the x-axis labels (e.g., atransf=exp; see also transf). If unspecified, no transformation is used.
-
targs
+
targs
optional arguments needed by the function specified via transf or atransf.
-
digits
+
digits
optional integer to specify the number of decimal places to which the tick mark labels of the x- and y-axis should be rounded. Can also be a vector of two integers, the first to specify the number of decimal places for the x-axis, the second for the y-axis labels (e.g., digits=c(2,3)). If unspecified, the function tries to set the argument to some sensible values.
-
cols
+
cols
vector with two or more colors for visualizing the order of the cumulative results.
-
grid
+
grid
logical to specify whether a grid should be added to the plot. Can also be a color name.
-
pch
+
pch
plotting symbol to use. By default, a filled circle is used. See points for other options.
character string to specify the heterogeneity measure to plot. Either "I2", "H2", "QE", "tau2", or "tau" (the last two only for random/mixed-effects models).
-
pch
+
pch
plotting symbol to use. By default, a borderless filled circle is used. See points for other options.
-
cex
+
cex
symbol expansion factor.
-
out
+
out
optional integer to specify the number of a study that may be a potential outlier. If specified, subsets containing the specified study are drawn in a different color than those not containing the study.
-
col
+
col
optional character string to specify the color of the points (if unspecified, points are drawn in black). When out is used, two colors should be specified (if unspecified, red is used for subsets containing the specified study and blue otherwise).
-
alpha
+
alpha
optional alpha transparency value for the points (0 means fully transparent and 1 means opaque). If unspecified, the function sets this to a sensible value.
-
border
+
border
optional character string to specify the color of the borders of the histogram bars. Set to FALSE to omit the borders.
-
xlim
+
xlim
x-axis limits. If unspecified, the function sets the x-axis limits to some sensible values.
-
ylim
+
ylim
y-axis limits. If unspecified, the function sets the y-axis limits to some sensible values.
-
xhist
+
xhist
logical to specify whether a histogram should be drawn for the x-axis (the default is TRUE).
-
yhist
+
yhist
logical to specify whether a histogram should be drawn for the y-axis (the default is TRUE).
-
hh
+
hh
numeric value (or vector of two values) to adjust the height of the histogram(s). Must be between 0 and 1, but should not be too close to 0 or 1, as otherwise the plot cannot be drawn.
-
breaks
+
breaks
optional argument passed on to hist for choosing the (number of) breakpoints of the histogram(s).
-
adjust
+
adjust
optional argument passed on to density for adjusting the bandwidth of the kernel density estimate(s) (values larger than 1 result in more smoothing).
-
lwd
+
lwd
optional numeric value to specify the line width of the estimated densities. Set to 0 to omit the line(s).
-
labels
+
labels
optional argument to specify the x-axis and y-axis labels (or passed on to pairs to specify the names of the variables in the scatter plot matrix).
# S3 method for class 'infl.rma.uni'plot(x, plotinf=TRUE, plotdfbs=FALSE, dfbsnew=FALSE, logcov=TRUE,layout, slab.style=1, las=0, pch=21, bg, bg.infl, col.na, ...)
Arguments
-
x
+
+
x
an object of class "infl.rma.uni" obtained with influence.
-
plotinf
+
plotinf
logical to specify whether the various case diagnostics should be plotted (the default is TRUE). Can also be a vector of up to 8 integers to specify which plots to draw. See ‘Details’ for the numbers corresponding to the various plots.
-
plotdfbs
+
plotdfbs
logical to specify whether the DFBETAS values should be plotted (the default is FALSE). Can also be a vector of integers to specify for which coefficient(s) to plot the DFBETAS values.
-
dfbsnew
+
dfbsnew
logical to specify whether a new device should be opened for plotting the DFBETAS values (the default is FALSE).
-
logcov
+
logcov
logical to specify whether the covariance ratios should be plotted on a log scale (the default is TRUE).
-
layout
+
layout
optional vector of two numbers to specify the number of rows and columns for the layout of the figure.
-
slab.style
+
slab.style
integer to specify the style of the x-axis labels: 1 = study number, 2 = study label, 3 = abbreviated study label. Note that study labels, even when abbreviated, may be too long to fit in the margins (see argument mar for par to adjust the margin sizes).
-
las
+
las
integer between 0 and 3 to specify the alignment of the axis labels (see par). The most useful alternative to 0 is 3, so that the x-axis labels are drawn vertical to the axis.
-
pch
+
pch
plotting symbol to use. By default, an open circle is used. See points for other options.
-
bg
+
bg
optional character string to specify the background color of open plotting symbols. If unspecified, gray is used by default.
-
bg.infl
+
bg.infl
optional character string to specify the background color when the point is considered influential. If unspecified, red is used by default.
-
col.na
+
col.na
optional character string to specify the color for lines connecting two points with NA values in between. If unspecified, a light shade of gray is used by default.
an object of class "permutest.rma.uni" obtained with permutest.
-
beta
+
beta
optional vector of indices to specify which (location) coefficients should be plotted.
-
alpha
+
alpha
optional vector of indices to specify which scale coefficients should be plotted. Only relevant for location-scale models (see rma.uni).
-
QM
+
QM
logical to specify whether the permutation distribution of the omnibus test of the (location) coefficients should be plotted (the default is FALSE).
-
QS
+
QS
logical to specify whether the permutation distribution of the omnibus test of the scale coefficients should be plotted (the default is FALSE). Only relevant for location-scale models (see rma.uni).
-
breaks
+
breaks
argument to be passed on to the corresponding argument of hist to set (the method for determining) the (number of) breakpoints.
-
freq
+
freq
logical to specify whether frequencies or probability densities should be plotted (the default is FALSE to plot densities).
-
col
+
col
optional character string to specify the color of the histogram bars.
-
border
+
border
optional character string to specify the color of the borders around the bars.
-
col.out
+
col.out
optional character string to specify the color of the bars that are more extreme than the observed test statistic (the default is a semi-transparent shade of red).
-
col.ref
+
col.ref
optional character string to specify the color of the theoretical reference/null distribution that is superimposed on top of the histogram (the default is a dark shade of gray).
-
col.density
+
col.density
optional character string to specify the color of the kernel density estimate of the permutation distribution that is superimposed on top of the histogram (the default is blue).
-
trim
+
trim
the fraction (up to 0.5) of observations to be trimmed from the tails of each permutation distribution before its histogram is plotted.
-
adjust
+
adjust
numeric value to be passed on to the corresponding argument of density (for adjusting the bandwidth of the kernel density estimate).
-
lwd
+
lwd
numeric vector to specify the width of the vertical lines corresponding to the value of the observed test statistic, of the theoretical reference/null distribution, of the density estimate, and of the vertical line at 0 (note: by default, the theoretical reference/null distribution and the density estimate both have a line width of 0 and are therefore not plotted).
-
layout
+
layout
optional vector of two numbers to specify the number of rows and columns for the layout of the figure.
-
legend
+
legend
logical to specify whether a legend should be added to the plot (the default is FALSE). Can also be a keyword to specify the position of the legend (see legend).
# S3 method for class 'rma.uni'plot(x, qqplot=FALSE, ...)
-# S3 method for rma.mh
+# S3 method for class 'rma.mh'plot(x, qqplot=FALSE, ...)
-# S3 method for rma.peto
+# S3 method for class 'rma.peto'plot(x, qqplot=FALSE, ...)
-# S3 method for rma.glmm
+# S3 method for class 'rma.glmm'plot(x, qqplot=FALSE, ...)
Arguments
-
x
+
+
x
an object of class "rma.uni", "rma.mh", or "rma.peto". The method is not yet implemented for objects of class "rma.glmm".
-
qqplot
+
qqplot
logical to specify whether a normal QQ plot should be drawn (the default is FALSE).
# S3 method for class 'rma.uni.selmodel'plot(x, xlim, ylim, n=1000, prec="max", scale=FALSE, ci=FALSE, reps=1000, shade=TRUE, rug=TRUE, add=FALSE, lty=c("solid","dotted"), lwd=c(2,1), ...)
@@ -103,46 +103,47 @@
Plot Method for 'plot.rma.uni.selmodel' Objects
Arguments
-
x
+
+
x
an object of class "rma.uni.selmodel" obtained with selmodel.
-
xlim
+
xlim
x-axis limits. Essentially the range of p-values for which the selection function should be drawn. If unspecified, the function sets the limits automatically.
-
ylim
+
ylim
y-axis limits. If unspecified, the function sets the limits automatically.
-
n
+
n
numeric value to specify for how many p-values within the x-axis limits the function value should be computed (the default is 1000).
-
prec
+
prec
either a character string (with options "max", "min", "mean", or "median") or a numeric value. See ‘Details’.
-
scale
+
scale
logical to specify whether the function values should be rescaled to a 0 to 1 range (the default is FALSE).
-
ci
+
ci
logical to specify whether a confidence interval should be drawn around the selection function (the default is FALSE). Can also be a string (with options "boot" or "wald"). See ‘Details’.
-
reps
+
reps
numeric value to specify the number of bootstrap samples to draw for generating the confidence interval bounds (the default is 1000).
-
shade
+
shade
logical to specify whether the confidence interval region should be shaded (the default is TRUE). Can also be a character vector to specify the color for the shading.
-
rug
+
rug
logical to specify whether the observed p-values should be added as tick marks on the x-axis (the default is TRUE).
-
add
+
add
logical to specify whether the function should be added to an existing plot (the default is FALSE).
-
lty
+
lty
the line types for the selection function and the confidence interval bounds.
-
lwd
+
lwd
the line widths for the selection function and the confidence interval bounds.
argument to be passed on to the corresponding argument of hist to set (the method for determining) the (number of) breakpoints.
-
freq
+
freq
logical to specify whether frequencies (if TRUE) or probability densities should be plotted (the default is FALSE).
-
col
+
col
optional character string to specify the color of the histogram bars.
-
border
+
border
optional character string to specify the color of the borders around the bars.
-
col.out
+
col.out
optional character string to specify the color of the bars that are more extreme than the observed (G)VIF value (the default is a semi-transparent shade of red).
-
col.density
+
col.density
optional character string to specify the color of the kernel density estimate of the distribution that is superimposed on top of the histogram (the default is blue).
-
trim
+
trim
the fraction (up to 0.5) of observations to be trimmed from the upper tail of each distribution before its histogram is plotted.
-
adjust
+
adjust
numeric value to be passed on to the corresponding argument of density (for adjusting the bandwidth of the kernel density estimate).
-
lwd
+
lwd
numeric vector to specify the width of the vertical lines corresponding to the value of the observed (G)VIFs and of the density estimate (note: by default, the density estimate has a line width of 0 and is therefore not plotted).
-
layout
+
layout
optional vector of two numbers to specify the number of rows and columns for the layout of the figure.
# S3 method for class 'rma'predict(object, newmods, intercept, tau2.levels, gamma2.levels, addx=FALSE,level, adjust=FALSE, digits, transf, targs, vcov=FALSE, ...)
-# S3 method for rma.ls
+# S3 method for class 'rma.ls'predict(object, newmods, intercept, addx=FALSE, newscale, addz=FALSE,level, adjust=FALSE, digits, transf, targs, vcov=FALSE, ...)
Arguments
-
object
+
+
object
an object of class "rma" or "rma.ls".
-
newmods
+
newmods
optional vector or matrix to specify the values of the moderator values for which the predicted values should be calculated. See ‘Details’.
-
intercept
+
intercept
logical to specify whether the intercept should be included when calculating the predicted values for newmods. If unspecified, the intercept is automatically added when the original model also included an intercept.
-
tau2.levels
+
tau2.levels
vector to specify the levels of the inner factor when computing prediction intervals. Only relevant for models of class "rma.mv" (see rma.mv) and when the model includes more than a single \(\tau^2\) value. See ‘Details’.
-
gamma2.levels
+
gamma2.levels
vector to specify the levels of the inner factor when computing prediction intervals. Only relevant for models of class "rma.mv" (see rma.mv) and when the model includes more than a single \(\gamma^2\) value. See ‘Details’.
-
addx
+
addx
logical to specify whether the values of the moderator variables should be added to the returned object. See ‘Examples’.
-
newscale
+
newscale
optional vector or matrix to specify the values of the scale variables for which the predicted values should be calculated. Only relevant for location-scale models (see rma.uni). See ‘Details’.
-
addz
+
addz
logical to specify whether the values of the scale variables should be added to the returned object.
-
level
+
level
numeric value between 0 and 100 to specify the confidence and prediction interval level (see here for details). If unspecified, the default is to take the value from the object.
-
adjust
+
adjust
logical to specify whether the width of confidence/prediction intervals should be adjusted using a Bonferroni correction (the default is FALSE).
-
digits
+
digits
optional integer to specify the number of decimal places to which the printed results should be rounded.
-
transf
+
transf
optional argument to specify a function to transform the predicted values and interval bounds (e.g., transf=exp; see also transf). If unspecified, no transformation is used.
-
targs
+
targs
optional arguments needed by the function specified under transf.
-
vcov
+
vcov
logical to specify whether the variance-covariance matrix of the predicted values should also be returned (the default is FALSE).
-
...
+
...
other arguments.
@@ -166,9 +167,7 @@
Details
Value
-
-
-
An object of class c("predict.rma","list.rma"). The object is a list containing the following components:
+
An object of class c("predict.rma","list.rma"). The object is a list containing the following components:
pred
predicted value(s).
@@ -204,8 +203,6 @@
Value
If vcov=TRUE, then the returned object is a list with the first element equal to the one as described above and the second element equal to the variance-covariance matrix of the predicted values.
-
-
The object is formatted and printed with the print function. To format the results as a data frame, one can use the as.data.frame function.
Print Methods for 'anova.rma' and 'list.anova.rma' Objects
-
+
print.anova.rma.Rd
@@ -95,21 +95,22 @@
Print Methods for 'anova.rma' and 'list.anova.rma' Objects
-
# S3 method for anova.rma
+
# S3 method for class 'anova.rma'print(x, digits=x$digits, ...)
-# S3 method for list.anova.rma
+# S3 method for class 'list.anova.rma'print(x, digits=x[[1]]$digits, ...)
Arguments
-
x
+
+
x
an object of class "anova.rma" or "list.anova.rma" obtained with anova.
-
digits
+
digits
integer to specify the number of decimal places to which the printed results should be rounded (the default is to take the value from the object).
Print Methods for 'confint.rma' and 'list.confint.rma' Objects
-
+
print.confint.rma.Rd
@@ -95,21 +95,22 @@
Print Methods for 'confint.rma' and 'list.confint.rma' Objects
-
# S3 method for confint.rma
+
# S3 method for class 'confint.rma'print(x, digits=x$digits, ...)
-# S3 method for list.confint.rma
+# S3 method for class 'list.confint.rma'print(x, digits=x$digits, ...)
Arguments
-
x
+
+
x
an object of class "confint.rma" or "list.confint.rma" obtained with confint.
-
digits
+
digits
integer to specify the number of decimal places to which the printed results should be rounded (the default is to take the value from the object).
integer to specify the number of decimal places to which the printed results should be rounded (the default is to take the value from the object).
-
out.names
+
out.names
character string with four elements to specify the variable names for the standard errors, test statistics, and lower/upper confidence interval bounds.
-
var.names
+
var.names
character string with two elements to specify the variable names for the observed effect sizes or outcomes and the sampling variances (the default is to take the value from the object if possible).
-
H0
+
H0
numeric value to specify the value of the effect size or outcome under the null hypothesis (the default is 0).
-
append
+
append
logical to specify whether the data frame specified via the object argument should be returned together with the additional variables that are calculated by the summary function (the default is TRUE).
-
replace
+
replace
logical to specify whether existing values for sei, zi, ci.lb, and ci.ub in the data frame should be replaced. Only relevant when the data frame already contains these variables. If replace=TRUE (the default), all of the existing values will be overwritten. If replace=FALSE, only NA values will be replaced.
-
level
+
level
numeric value between 0 and 100 to specify the confidence interval level (the default is 95; see here for details).
-
olim
+
olim
optional argument to specify observation/outcome limits. If unspecified, no limits are used.
-
transf
+
transf
optional argument to specify a function to transform the observed effect sizes or outcomes and interval bounds (e.g., transf=exp; see also transf). If unspecified, no transformation is used. Any additional arguments needed for the function specified here can be passed via ....
-
...
+
...
other arguments.
Value
-
-
-
The print.escalc function formats and prints the data frame, so that the observed effect sizes or outcomes and sampling variances are rounded (to the number of digits specified).
-
-
+
The print.escalc function formats and prints the data frame, so that the observed effect sizes or outcomes and sampling variances are rounded (to the number of digits specified).
The summary.escalc function creates an object that is a data frame containing the original data (if append=TRUE) and the following components:
yi
observed effect sizes or outcomes (transformed if transf is specified).
@@ -173,11 +170,7 @@
Value
When the transf argument is specified, elements vi, sei, zi, and pval are not included (since these only apply to the untransformed effect sizes or outcomes).
-
-
Note that the actual variable names above depend on the out.names (and var.names) arguments. If the data frame already contains variables with names as specified by the out.names argument, the values for these variables will be overwritten when replace=TRUE (which is the default). By setting replace=FALSE, only values that are NA will be replaced.
-
-
The print.escalc function again formats and prints the data frame, rounding the added variables to the number of digits specified.
# S3 method for class 'list.rma'print(x, digits=x$digits, ...)
Arguments
-
x
+
+
x
an object of class "list.rma".
-
digits
+
digits
integer to specify the number of decimal places to which the printed results should be rounded (the default is to take the value from the object).
-
...
+
...
other arguments.
Value
-
-
-
See the documentation of the function that creates the "list.rma" object for details on what is printed. Regardless of what is printed, a data frame with the results is also returned invisibly.
-
-
+
See the documentation of the function that creates the "list.rma" object for details on what is printed. Regardless of what is printed, a data frame with the results is also returned invisibly.
See methods.list.rma for some additional method functions for "list.rma" objects.
# S3 method for class 'matreg'print(x, digits, signif.stars=getOption("show.signif.stars"), signif.legend=signif.stars, ...)
-# S3 method for matreg
+# S3 method for class 'matreg'summary(object, digits, ...)
-# S3 method for summary.matreg
+# S3 method for class 'summary.matreg'print(x, digits, signif.stars=getOption("show.signif.stars"), signif.legend=signif.stars, ...)
Arguments
-
x
+
+
x
an object of class "matreg" or "summary.matreg" (for print).
-
object
+
object
an object of class "matreg" (for summary).
-
digits
+
digits
integer to specify the number of decimal places to which the printed results should be rounded. If unspecified, the default is to take the value from the object.
-
signif.stars
+
signif.stars
logical to specify whether p-values should be encoded visually with ‘significance stars’. Defaults to the show.signif.stars slot of options.
-
signif.legend
+
signif.legend
logical to specify whether the legend for the ‘significance stars’ should be printed. Defaults to the value for signif.stars.
# S3 method for class 'regtest'print(x, digits=x$digits, ret.fit=x$ret.fit, ...)
Arguments
-
x
+
+
x
an object of class "regtest" obtained with regtest.
-
digits
+
digits
integer to specify the number of decimal places to which the printed results should be rounded (the default is to take the value from the object).
-
ret.fit
+
ret.fit
logical to specify whether the full results from the fitted model should also be returned. If unspecified, the default is to take the value from the object.
# S3 method for class 'rma.uni'print(x, digits, showfit=FALSE, signif.stars=getOption("show.signif.stars"), signif.legend=signif.stars, ...)
-# S3 method for rma.mh
+# S3 method for class 'rma.mh'print(x, digits, showfit=FALSE, ...)
-# S3 method for rma.peto
+# S3 method for class 'rma.peto'print(x, digits, showfit=FALSE, ...)
-# S3 method for rma.glmm
+# S3 method for class 'rma.glmm'print(x, digits, showfit=FALSE, signif.stars=getOption("show.signif.stars"), signif.legend=signif.stars, ...)
-# S3 method for rma.mv
+# S3 method for class 'rma.mv'print(x, digits, showfit=FALSE, signif.stars=getOption("show.signif.stars"), signif.legend=signif.stars, ...)
-# S3 method for rma
+# S3 method for class 'rma'summary(object, digits, ...)
-# S3 method for summary.rma
+# S3 method for class 'summary.rma'print(x, digits, showfit=TRUE, signif.stars=getOption("show.signif.stars"), signif.legend=signif.stars, ...)
Arguments
-
x
+
+
x
an object of class "rma.uni", "rma.mh", "rma.peto", "rma.glmm", "rma.mv", or "summary.rma" (for print).
-
object
+
object
an object of class "rma" (for summary).
-
digits
+
digits
integer to specify the number of decimal places to which the printed results should be rounded. If unspecified, the default is to take the value from the object. See also here for further details on how to control the number of digits in the output.
-
showfit
+
showfit
logical to specify whether the fit statistics and information criteria should be printed (the default is FALSE for print and TRUE for summary).
-
signif.stars
+
signif.stars
logical to specify whether p-values should be encoded visually with ‘significance stars’. Defaults to the show.signif.stars slot of options.
-
signif.legend
+
signif.legend
logical to specify whether the legend for the ‘significance stars’ should be printed. Defaults to the value for signif.stars.
-
...
+
...
other arguments.
@@ -163,9 +164,7 @@
Details
Value
-
-
-
The print functions do not return an object. The summary function returns the object passed to it (with additional class "summary.rma").
+
The print functions do not return an object. The summary function returns the object passed to it (with additional class "summary.rma").
# S3 method for class 'rma.uni'profile(fitted, xlim, ylim, steps=20, lltol=1e-03, progbar=TRUE, parallel="no", ncpus=1, cl, plot=TRUE, ...)
-# S3 method for rma.mv
+# S3 method for class 'rma.mv'profile(fitted, sigma2, tau2, rho, gamma2, phi, xlim, ylim, steps=20, lltol=1e-03, progbar=TRUE, parallel="no", ncpus=1, cl, plot=TRUE, ...)
-# S3 method for rma.uni.selmodel
+# S3 method for class 'rma.uni.selmodel'profile(fitted, tau2, delta, xlim, ylim, steps=20, lltol=1e-03, progbar=TRUE, parallel="no", ncpus=1, cl, plot=TRUE, ...)
-# S3 method for rma.ls
+# S3 method for class 'rma.ls'profile(fitted, alpha, xlim, ylim, steps=20, lltol=1e-03, progbar=TRUE, parallel="no", ncpus=1, cl, plot=TRUE, ...)
-# S3 method for profile.rma
+# S3 method for class 'profile.rma'print(x, ...)
-# S3 method for profile.rma
+# S3 method for class 'profile.rma'plot(x, xlim, ylim, pch=19, xlab, ylab, main, refline=TRUE, cline=FALSE, ...)
Arguments
-
fitted
+
+
fitted
an object of class "rma.uni", "rma.mv", "rma.uni.selmodel", or "rma.ls".
-
x
+
x
an object of class "profile.rma" (for plot and print).
-
sigma2
+
sigma2
optional integer to specify for which \(\sigma^2\) parameter the likelihood should be profiled.
-
tau2
+
tau2
optional integer to specify for which \(\tau^2\) parameter the likelihood should be profiled.
-
rho
+
rho
optional integer to specify for which \(\rho\) parameter the likelihood should be profiled.
-
gamma2
+
gamma2
optional integer to specify for which \(\gamma^2\) parameter the likelihood should be profiled.
-
phi
+
phi
optional integer to specify for which \(\phi\) parameter the likelihood should be profiled.
-
delta
+
delta
optional integer to specify for which \(\delta\) parameter the likelihood should be profiled.
-
alpha
+
alpha
optional integer to specify for which \(\alpha\) parameter the likelihood should be profiled.
-
xlim
+
xlim
optional vector to specify the lower and upper limit of the parameter over which the profiling should be done. If unspecified, the function sets these limits automatically.
-
ylim
+
ylim
optional vector to specify the y-axis limits when plotting the profiled likelihood. If unspecified, the function sets these limits automatically.
-
steps
+
steps
number of points between xlim[1] and xlim[2] (inclusive) for which the likelihood should be evaluated (the default is 20). Can also be a numeric vector of length 2 or longer to specify for which parameter values the likelihood should be evaluated (in this case, xlim is automatically set to range(steps) if unspecified).
-
lltol
+
lltol
numerical tolerance used when comparing values of the profiled log-likelihood with the log-likelihood of the fitted model (the default is 1e-03).
-
progbar
+
progbar
logical to specify whether a progress bar should be shown (the default is TRUE).
-
parallel
+
parallel
character string to specify whether parallel processing should be used (the default is "no"). For parallel processing, set to either "snow" or "multicore". See ‘Details’.
-
ncpus
+
ncpus
integer to specify the number of processes to use in the parallel processing.
-
cl
+
cl
optional cluster to use if parallel="snow". If unspecified, a cluster on the local machine is created for the duration of the call.
-
plot
+
plot
logical to specify whether the profile plot should be drawn after profiling is finished (the default is TRUE).
-
pch
+
pch
plotting symbol to use. By default, a filled circle is used. See points for other options.
-
refline
+
refline
logical to specify whether the value of the parameter estimate should be indicated by a dotted vertical line and its log-likelihood value by a dotted horizontal line (the default is TRUE).
-
cline
+
cline
logical to specify whether a horizontal reference line should be added to the plot that indicates the log-likelihood value corresponding to the 95% profile confidence interval (the default is FALSE). Can also be a numeric value between 0 and 100 to specify the confidence interval level.
-
xlab
+
xlab
title for the x-axis. If unspecified, the function sets an appropriate axis title.
-
ylab
+
ylab
title for the y-axis. If unspecified, the function sets an appropriate axis title.
-
main
+
main
title for the plot. If unspecified, the function sets an appropriate title.
# S3 method for class 'rma.uni'qqnorm(y, type="rstandard", pch=21, col, bg, envelope=TRUE, level=y$level, bonferroni=FALSE, reps=1000, smooth=TRUE, bass=0, label=FALSE, offset=0.3, pos=13, lty, ...)
-# S3 method for rma.mh
+# S3 method for class 'rma.mh'qqnorm(y, type="rstandard", pch=21, col, bg, label=FALSE, offset=0.3, pos=13, ...)
-# S3 method for rma.peto
+# S3 method for class 'rma.peto'qqnorm(y, type="rstandard", pch=21, col, bg, label=FALSE, offset=0.3, pos=13, ...)
-# S3 method for rma.glmm
+# S3 method for class 'rma.glmm'qqnorm(y, ...)
-# S3 method for rma.mv
+# S3 method for class 'rma.mv'qqnorm(y, ...)
Arguments
-
y
+
+
y
an object of class "rma.uni", "rma.mh", or "rma.peto". The method is not yet implemented for objects of class "rma.glmm" or "rma.mv".
-
type
+
type
character string (either "rstandard" (default) or "rstudent") to specify whether standardized residuals or studentized deleted residuals should be used in creating the plot. See ‘Details’.
-
pch
+
pch
plotting symbol to use for the observed outcomes. By default, an open circle is used. See points for other options.
-
col
+
col
optional character string to specify the (border) color of the points.
-
bg
+
bg
optional character string to specify the background color of open plot symbols.
-
envelope
+
envelope
logical to specify whether a pseudo confidence envelope should be simulated and added to the plot (the default is TRUE)). Only for objects of class "rma.uni". See ‘Details’.
-
level
+
level
numeric value between 0 and 100 to specify the level of the pseudo confidence envelope (see here for details). The default is to take the value from the object.
-
bonferroni
+
bonferroni
logical to specify whether the bounds of the envelope should be Bonferroni corrected.
-
reps
+
reps
numeric value to specify the number of iterations for simulating the pseudo confidence envelope (the default is 1000).
-
smooth
+
smooth
logical to specify whether the results from the simulation should be smoothed (the default is TRUE).
-
bass
+
bass
numeric value that controls the degree of smoothing (the default is 0).
-
label
+
label
argument to control the labeling of the points (the default is FALSE). See ‘Details’.
-
offset
+
offset
argument to control the distance between the points and the corresponding labels.
-
pos
+
pos
argument to control the position of the labels.
-
lty
+
lty
optional character string to specify the line type for the diagonal line and the pseudo confidence envelope. If unspecified, the function sets this to c("solid", "dotted") by default.
-
...
+
...
other arguments.
@@ -169,9 +170,7 @@
Details
Value
-
-
-
A list with components:
+
A list with components:
x
the x-axis coordinates of the points that were plotted.
logical to specify whether the plot should be centered horizontally at the model estimate (the default is FALSE).
-
xlim
+
xlim
x-axis limits. If unspecified, the function sets the x-axis limits to some sensible values.
-
zlim
+
zlim
z-axis limits. If unspecified, the function sets the z-axis limits to some sensible values (note that the z-axis limits are the actual vertical limit of the plotting region).
-
xlab
+
xlab
title for the x-axis. If unspecified, the function sets an appropriate axis title.
-
zlab
+
zlab
title for the z-axis. If unspecified, the function sets an appropriate axis title.
-
atz
+
atz
position for the z-axis tick marks and labels. If unspecified, these values are set by the function.
-
aty
+
aty
position for the y-axis tick marks and labels. If unspecified, these values are set by the function.
-
steps
+
steps
the number of tick marks for the y-axis (the default is 7). Ignored when argument aty is used.
-
level
+
level
numeric value between 0 and 100 to specify the level of the z-axis error region. The default is to take the value from the object.
-
digits
+
digits
integer to specify the number of decimal places to which the tick mark labels of the y-axis should be rounded (the default is 2).
-
transf
+
transf
argument to specify a function to transform the y-axis labels (e.g., transf=exp; see also transf). If unspecified, no transformation is used.
-
targs
+
targs
optional arguments needed by the function specified via transf.
-
pch
+
pch
plotting symbol. By default, an open circle is used. See points for other options.
-
col
+
col
character string to specify the (border) color of the points.
-
bg
+
bg
character string to specify the background color of open plot symbols.
-
back
+
back
character string to specify the background color of the z-axis error region. If unspecified, a shade of gray is used. Set to NA to suppress shading of the region.
-
arc.res
+
arc.res
integer to specify the number of line segments (i.e., the resolution) when drawing the y-axis and confidence interval arcs (the default is 100).
-
cex
+
cex
symbol expansion factor.
-
cex.lab
+
cex.lab
character expansion factor for axis labels.
-
cex.axis
+
cex.axis
character expansion factor for axis annotations.
-
...
+
...
other arguments.
@@ -186,9 +187,7 @@
Details
Value
-
-
-
A data frame with components:
+
A data frame with components:
x
the x-axis coordinates of the points that were plotted.
Best Linear Unbiased Predictions for 'rma.uni' and 'rma.mv' Objects
-
+
ranef.Rd
@@ -95,41 +95,40 @@
Best Linear Unbiased Predictions for 'rma.uni' and 'rma.mv' Objects
-
# S3 method for rma.uni
+
# S3 method for class 'rma.uni'ranef(object, level, digits, transf, targs, ...)
-# S3 method for rma.mv
+# S3 method for class 'rma.mv'ranef(object, level, digits, transf, targs, verbose=FALSE, ...)
Arguments
-
object
+
+
object
an object of class "rma.uni" or "rma.mv".
-
level
+
level
numeric value between 0 and 100 to specify the prediction interval level (see here for details). If unspecified, the default is to take the value from the object.
-
digits
+
digits
optional integer to specify the number of decimal places to which the printed results should be rounded. If unspecified, the default is to take the value from the object.
-
transf
+
transf
optional argument to specify a function to transform the predicted values and interval bounds (e.g., transf=exp; see also transf). If unspecified, no transformation is used.
-
targs
+
targs
optional arguments needed by the function specified under transf.
-
verbose
+
verbose
logical to specify whether output should be generated on the progress of the computations (the default is FALSE).
-
...
+
...
other arguments.
Value
-
-
-
For objects of class "rma.uni", an object of class "list.rma". The object is a list containing the following components:
+
For objects of class "rma.uni", an object of class "list.rma". The object is a list containing the following components:
pred
predicted values.
@@ -147,8 +146,6 @@
Value
The object is formatted and printed with the print function. To format the results as a data frame, one can use the as.data.frame function.
-
-
For objects of class "rma.mv", a list of data frames with the same components as described above.
Calculate the Variance-Covariance of Dependent Correlation Coefficients
-
+
rcalc.Rd
@@ -100,25 +100,26 @@
Calculate the Variance-Covariance of Dependent Correlation Coefficients
Arguments
-
x
+
+
x
a formula of the form ri ~ var1 + var2 | study. Can also be a correlation matrix or list thereof. See ‘Details’.
-
ni
+
ni
vector to specify the sample sizes based on which the correlations were computed.
-
data
+
data
data frame containing the variables specified via the formula (and the sample sizes).
-
rtoz
+
rtoz
logical to specify whether to transform the correlations via Fisher's r-to-z transformation (the default is FALSE).
-
nfun
+
nfun
a character string to specify how the ‘common’ sample size within each study should be computed. Possible options are "min" (for the minimum), "harmonic" (for the harmonic mean), or "mean" (for the arithmetic mean). Can also be a function. See ‘Details’.
-
sparse
+
sparse
logical to specify whether the variance-covariance matrix should be returned as a sparse matrix (the default is FALSE).
-
...
+
...
other arguments.
@@ -135,9 +136,7 @@
Details
Value
-
-
-
A list containing the following components:
+
A list containing the following components:
dat
a data frame with the study identifier, the two variable identifiers, a variable pair identifier, the correlation coefficients (possibly transformed with Fisher's r-to-z transformation), and the (common) sample sizes.
grid=FALSE, refline, label=FALSE, offset=c(1,1), labsize=1,lcol, lwd, lty, legend=FALSE, xvals, ...)
-# S3 method for regplot
+# S3 method for class 'regplot'points(x, ...)
Arguments
-
x
+
+
x
an object of class "rma.uni", "rma.mv", or "rma.glmm" including one or multiple moderators (or an object of class "regplot" for points).
-
mod
+
mod
either a scalar to specify the position of the moderator variable in the model or a character string to specify the name of the moderator variable.
-
pred
+
pred
logical to specify whether the (marginal) regression line based on the moderator should be added to the plot (the default is TRUE). Can also be an object from predict. See ‘Details’.
-
ci
+
ci
logical to specify whether the corresponding confidence interval bounds should be added to the plot (the default is TRUE).
-
pi
+
pi
logical to specify whether the corresponding prediction interval bounds should be added to the plot (the default is FALSE).
-
shade
+
shade
logical to specify whether the confidence/prediction interval regions should be shaded (the default is TRUE). Can also be a two-element character vector to specify the colors for shading the confidence and prediction interval regions (if shading only the former, a single color can also be specified).
-
xlim
+
xlim
x-axis limits. If unspecified, the function sets the x-axis limits to some sensible values.
-
ylim
+
ylim
y-axis limits. If unspecified, the function sets the y-axis limits to some sensible values.
-
predlim
+
predlim
optional argument to specify the limits of the (marginal) regression line. If unspecified, the limits are based on the range of the moderator variable.
-
olim
+
olim
optional argument to specify observation/outcome limits. If unspecified, no limits are used.
-
xlab
+
xlab
title for the x-axis. If unspecified, the function sets an appropriate axis title.
-
ylab
+
ylab
title for the y-axis. If unspecified, the function sets an appropriate axis title.
-
at
+
at
position of the y-axis tick marks and corresponding labels. If unspecified, the function sets the tick mark positions/labels to some sensible values.
-
digits
+
digits
integer to specify the number of decimal places to which the tick mark labels of the y-axis should be rounded. When specifying an integer (e.g., 2L), trailing zeros after the decimal mark are dropped for the y-axis labels. When specifying a numeric value (e.g., 2), trailing zeros are retained.
-
transf
+
transf
optional argument to specify a function to transform the observed outcomes, predicted values, and confidence/prediction interval bounds (e.g., transf=exp; see also transf). If unspecified, no transformation is used.
-
atransf
+
atransf
optional argument to specify a function to transform the y-axis labels (e.g., atransf=exp; see also transf). If unspecified, no transformation is used.
-
targs
+
targs
optional arguments needed by the function specified via transf or atransf.
-
level
+
level
numeric value between 0 and 100 to specify the confidence/prediction interval level (see here for details). The default is to take the value from the object.
-
pch
+
pch
plotting symbol to use for the observed outcomes. By default, an open circle is used. Can also be a vector of values. See points for other options.
-
psize
+
psize
optional numeric value to specify the point sizes for the observed outcomes. If unspecified, the point sizes are a function of the model weights. Can also be a vector of values. Can also be a character string (either "seinv" or "vinv") to make the point sizes proportional to the inverse standard errors or inverse sampling variances.
-
plim
+
plim
numeric vector of length 2 to scale the point sizes (ignored when a numeric value or vector is specified for psize). See ‘Details’.
-
col
+
col
character string to specify the (border) color of the points. Can also be a vector.
-
bg
+
bg
character string to specify the background color of open plot symbols. Can also be a vector.
-
slab
+
slab
optional vector with labels for the \(k\) studies. If unspecified, the function tries to extract study labels from x.
-
grid
+
grid
logical to specify whether a grid should be added to the plot. Can also be a color name for the grid.
-
refline
+
refline
optional numeric value to specify the location of a horizontal reference line that should be added to the plot.
-
label
+
label
argument to control the labeling of the points (the default is FALSE). See ‘Details’.
-
offset
+
offset
argument to control the distance between the points and the corresponding labels. See ‘Details’.
-
labsize
+
labsize
numeric value to control the size of the labels.
-
lcol
+
lcol
optional vector of (up to) four elements to specify the color of the regression line, of the confidence interval bounds, of the prediction interval bounds, and of the horizontal reference line.
-
lty
+
lty
optional vector of (up to) four elements to specify the line type of the regression line, of the confidence interval bounds, of the prediction interval bounds, and of the horizontal reference line.
-
lwd
+
lwd
optional vector of (up to) four elements to specify the line width of the regression line, of the confidence interval bounds, of the prediction interval bounds, and of the horizontal reference line.
-
legend
+
legend
logical to specify whether a legend should be added to the plot (the default is FALSE). Can also be a keyword to specify the position of the legend (see legend).
-
xvals
+
xvals
optional numeric vector to specify the values of the moderator for which predicted values should be computed. Needs to be specified when passing an object from predict to the pred argument. See ‘Details’.
Dynamically Generated Analysis Reports for 'rma.uni' Objects
-
+
reporter.Rd
@@ -97,44 +97,45 @@
Dynamically Generated Analysis Reports for 'rma.uni' Objects
reporter(x, ...)
-# S3 method for rma.uni
+# S3 method for class 'rma.uni'reporter(x, dir, filename, format="html_document", open=TRUE,digits, forest, funnel, footnotes=FALSE, verbose=TRUE, ...)
Arguments
-
x
+
+
x
an object of class "rma.uni".
-
dir
+
dir
optional character string to specify the directory for creating the report. If unspecified, tempdir will be used.
-
filename
+
filename
optional character string to specify the filename (without file extension) for the report. If unspecified, the function sets a filename automatically.
-
format
+
format
output format for the report (either html_document, pdf_document, or word_document). Can be abbreviated. See ‘Note’.
-
open
+
open
logical to specify whether the report should be opened after it has been generated (the default is TRUE). See ‘Note’.
-
digits
+
digits
optional integer to specify the number of decimal places to which the printed results should be rounded. If unspecified, the default is to take the value from the object.
-
forest
+
forest
either a logical which will suppress the drawing of the forest plot when set to FALSE or a character string with arguments to be added to the call to forest for generating the forest plot.
-
funnel
+
funnel
either a logical which will suppress the drawing of the funnel plot when set to FALSE or a character string with arguments to be added to the call to funnel for generating the funnel plot.
-
footnotes
+
footnotes
logical to specify whether additional explanatory footnotes should be added to the report (the default is FALSE).
-
verbose
+
verbose
logical to specify whether information on the progress of the report generation should be provided (the default is TRUE).
-
...
+
...
other arguments.
@@ -144,9 +145,7 @@
Details
Value
-
-
-
The function generates either a html, pdf, or docx file and returns (invisibly) the path to the generated document.
+
The function generates either a html, pdf, or docx file and returns (invisibly) the path to the generated document.
Note
@@ -185,12 +184,12 @@
Examples
### generate reportreporter(res)#>
-#> Directory for generating the report is: /tmp/RtmpsKqr8i
+#> Directory for generating the report is: /tmp/RtmpcUg4X8#> Copying references.bib and apa.csl to report directory ...#> Saving model object to report_res.rdata ...#> Creating report_res.rmd file ...#> Rendering report_res.rmd file ...
-#> Generated /tmp/RtmpsKqr8i/report_res.html ...
+#> Generated /tmp/RtmpcUg4X8/report_res.html ...#> Opening report ...
# S3 method for class 'rma'residuals(object, type="response", ...)
-# S3 method for rma.uni
+# S3 method for class 'rma.uni'rstandard(model, digits, type="marginal", ...)
-# S3 method for rma.mh
+# S3 method for class 'rma.mh'rstandard(model, digits, ...)
-# S3 method for rma.peto
+# S3 method for class 'rma.peto'rstandard(model, digits, ...)
-# S3 method for rma.mv
+# S3 method for class 'rma.mv'rstandard(model, digits, cluster, ...)
-# S3 method for rma.uni
+# S3 method for class 'rma.uni'rstudent(model, digits, progbar=FALSE, ...)
-# S3 method for rma.mh
+# S3 method for class 'rma.mh'rstudent(model, digits, progbar=FALSE, ...)
-# S3 method for rma.peto
+# S3 method for class 'rma.peto'rstudent(model, digits, progbar=FALSE, ...)
-# S3 method for rma.mv
+# S3 method for class 'rma.mv'rstudent(model, digits, progbar=FALSE, cluster, reestimate=TRUE, parallel="no", ncpus=1, cl, ...)
Arguments
-
object
+
+
object
an object of class "rma" (for residuals).
-
type
+
type
the type of residuals which should be returned. For residuals, the alternatives are: "response" (default), "rstandard", "rstudent", and "pearson". For rstandard.rma.uni, the alternatives are: "marginal" (default) and "conditional". See ‘Details’.
-
model
+
model
an object of class "rma" (for residuals) or an object of class "rma.uni", "rma.mh", "rma.peto", or "rma.mv" (for rstandard and rstudent).
-
cluster
+
cluster
optional vector to specify a clustering variable to use for computing cluster-level multivariate standardized residuals (only for "rma.mv" objects).
-
reestimate
+
reestimate
logical to specify whether variance/correlation components should be re-estimated after deletion of the \(i\textrm{th}\) case when computing externally standardized residuals for "rma.mv" objects (the default is TRUE).
-
parallel
+
parallel
character string to specify whether parallel processing should be used (the default is "no"). For parallel processing, set to either "snow" or "multicore". See ‘Note’.
-
ncpus
+
ncpus
integer to specify the number of processes to use in the parallel processing.
-
cl
+
cl
optional cluster to use if parallel="snow". If unspecified, a cluster on the local machine is created for the duration of the call.
-
digits
+
digits
optional integer to specify the number of decimal places to which the printed results should be rounded. If unspecified, the default is to take the value from the object.
-
progbar
+
progbar
logical to specify whether a progress bar should be shown (only for rstudent) (the default is FALSE).
-
...
+
...
other arguments.
@@ -167,9 +168,7 @@
Details
Value
-
-
-
Either a vector with the residuals of the requested type (for residuals) or an object of class "list.rma", which is a list containing the following components:
+
Either a vector with the residuals of the requested type (for residuals) or an object of class "list.rma", which is a list containing the following components:
resid
observed residuals (for rstandard) or deleted residuals (for rstudent).
Meta-Analysis via Generalized Linear (Mixed-Effects) Models
-
+
rma.glmm.Rd
@@ -104,118 +104,119 @@
Meta-Analysis via Generalized Linear (Mixed-Effects) Models
Arguments
-
ai
+
+
ai
see below and the documentation of the escalc function for more details.
-
bi
+
bi
see below and the documentation of the escalc function for more details.
-
ci
+
ci
see below and the documentation of the escalc function for more details.
-
di
+
di
see below and the documentation of the escalc function for more details.
-
n1i
+
n1i
see below and the documentation of the escalc function for more details.
-
n2i
+
n2i
see below and the documentation of the escalc function for more details.
-
x1i
+
x1i
see below and the documentation of the escalc function for more details.
-
x2i
+
x2i
see below and the documentation of the escalc function for more details.
-
t1i
+
t1i
see below and the documentation of the escalc function for more details.
-
t2i
+
t2i
see below and the documentation of the escalc function for more details.
-
xi
+
xi
see below and the documentation of the escalc function for more details.
-
mi
+
mi
see below and the documentation of the escalc function for more details.
-
ti
+
ti
see below and the documentation of the escalc function for more details.
-
ni
+
ni
see below and the documentation of the escalc function for more details.
-
mods
+
mods
optional argument to include one or more moderators in the model. A single moderator can be given as a vector of length \(k\) specifying the values of the moderator. Multiple moderators are specified by giving a matrix with \(k\) rows and as many columns as there are moderator variables. Alternatively, a model formula can be used to specify the model. See ‘Details’.
-
measure
+
measure
character string to specify the outcome measure to use for the meta-analysis. Possible options are "OR" for the (log transformed) odds ratio, "IRR" for the (log transformed) incidence rate ratio, "PLO" for the (logit transformed) proportion, or "IRLN" for the (log transformed) incidence rate.
-
intercept
+
intercept
logical to specify whether an intercept should be added to the model (the default is TRUE).
-
data
+
data
optional data frame containing the data supplied to the function.
-
slab
+
slab
optional vector with labels for the \(k\) studies.
-
subset
+
subset
optional (logical or numeric) vector to specify the subset of studies that should be used for the analysis.
-
add
+
add
non-negative number to specify the amount to add to zero cells, counts, or frequencies when calculating the observed effect sizes or outcomes of the individual studies. See below and the documentation of the escalc function for more details.
-
to
+
to
character string to specify when the values under add should be added (either "only0", "all", "if0all", or "none"). See below and the documentation of the escalc function for more details.
-
drop00
+
drop00
logical to specify whether studies with no cases/events (or only cases) in both groups should be dropped. See the documentation of the escalc function for more details.
-
vtype
+
vtype
character string to specify the type of sampling variances to calculate when calculating the observed effect sizes or outcomes. See the documentation of the escalc function for more details.
-
model
+
model
character string to specify the general model type for the analysis. Either "UM.FS" (the default), "UM.RS", "CM.EL", or "CM.AL". See ‘Details’.
-
method
+
method
character string to specify whether an equal- or a random-effects model should be fitted. An equal-effects model is fitted when using method="EE". A random-effects model is fitted by setting method="ML" (the default). See ‘Details’.
-
coding
+
coding
numeric scalar to specify how the group variable should be coded in the random effects structure for random/mixed-effects models (the default is 1/2). See ‘Note’.
-
cor
+
cor
logical to specify whether the random study effects should be allowed to be correlated with the random group effects for random/mixed-effects models when model="UM.RS" (the default is FALSE). See ‘Note’.
-
test
+
test
character string to specify how test statistics and confidence intervals for the fixed effects should be computed. By default (test="z"), Wald-type tests and CIs are obtained, which are based on a standard normal distribution. When test="t", a t-distribution is used instead. See ‘Details’ and also here for some recommended practices.
-
level
+
level
numeric value between 0 and 100 to specify the confidence interval level (the default is 95; see here for details).
-
btt
+
btt
optional vector of indices to specify which coefficients to include in the omnibus test of moderators. Can also be a string to grep for. See ‘Details’.
-
nAGQ
+
nAGQ
positive integer to specify the number of points per axis for evaluating the adaptive Gauss-Hermite approximation to the log-likelihood. The default is 7. Setting this to 1 corresponds to the Laplacian approximation. See ‘Note’.
-
verbose
+
verbose
logical to specify whether output should be generated on the progress of the model fitting (the default is FALSE). Can also be an integer. Values > 1 generate more verbose output. See ‘Note’.
-
digits
+
digits
optional integer to specify the number of decimal places to which the printed results should be rounded. If unspecified, the default is 4. See also here for further details on how to control the number of digits in the output.
-
control
+
control
optional list of control values for the estimation algorithms. If unspecified, default values are defined inside the function. See ‘Note’.
-
...
+
...
additional arguments.
Details
-
+
Specifying the Data
@@ -305,9 +306,7 @@
Observed Ef
Value
-
-
-
An object of class c("rma.glmm","rma"). The object is a list containing the following components:
+
An object of class c("rma.glmm","rma"). The object is a list containing the following components:
vector with the \(2 \times 2\) table frequencies (upper left cell). See below and the documentation of the escalc function for more details.
-
bi
+
bi
vector with the \(2 \times 2\) table frequencies (upper right cell). See below and the documentation of the escalc function for more details.
-
ci
+
ci
vector with the \(2 \times 2\) table frequencies (lower left cell). See below and the documentation of the escalc function for more details.
-
di
+
di
vector with the \(2 \times 2\) table frequencies (lower right cell). See below and the documentation of the escalc function for more details.
-
n1i
+
n1i
vector with the group sizes or row totals (first group). See below and the documentation of the escalc function for more details.
-
n2i
+
n2i
vector with the group sizes or row totals (second group). See below and the documentation of the escalc function for more details.
-
x1i
+
x1i
vector with the number of events (first group). See below and the documentation of the escalc function for more details.
-
x2i
+
x2i
vector with the number of events (second group). See below and the documentation of the escalc function for more details.
-
t1i
+
t1i
vector with the total person-times (first group). See below and the documentation of the escalc function for more details.
-
t2i
+
t2i
vector with the total person-times (second group). See below and the documentation of the escalc function for more details.
-
measure
+
measure
character string to specify the outcome measure to use for the meta-analysis. Possible options are "RR" for the (log transformed) risk ratio, "OR" for the (log transformed) odds ratio, "RD" for the risk difference, "IRR" for the (log transformed) incidence rate ratio, or "IRD" for the incidence rate difference.
-
data
+
data
optional data frame containing the data supplied to the function.
-
slab
+
slab
optional vector with labels for the \(k\) studies.
-
subset
+
subset
optional (logical or numeric) vector to specify the subset of studies that should be used for the analysis.
-
add
+
add
non-negative number to specify the amount to add to zero cells or even counts when calculating the observed effect sizes of the individual studies. Can also be a vector of two numbers, where the first number is used in the calculation of the observed effect sizes and the second number is used when applying the Mantel-Haenszel method. See below and the documentation of the escalc function for more details.
-
to
+
to
character string to specify when the values under add should be added (either "only0", "all", "if0all", or "none"). Can also be a character vector, where the first string again applies when calculating the observed effect sizes or outcomes and the second string when applying the Mantel-Haenszel method. See below and the documentation of the escalc function for more details.
-
drop00
+
drop00
logical to specify whether studies with no cases/events (or only cases) in both groups should be dropped when calculating the observed effect sizes or outcomes (the outcomes for such studies are set to NA). Can also be a vector of two logicals, where the first applies to the calculation of the observed effect sizes or outcomes and the second when applying the Mantel-Haenszel method. See below and the documentation of the escalc function for more details.
-
correct
+
correct
logical to specify whether to apply a continuity correction when computing the Cochran-Mantel-Haenszel test statistic.
-
level
+
level
numeric value between 0 and 100 to specify the confidence interval level (the default is 95; see here for details).
-
verbose
+
verbose
logical to specify whether output should be generated on the progress of the model fitting (the default is FALSE).
-
digits
+
digits
optional integer to specify the number of decimal places to which the printed results should be rounded. If unspecified, the default is 4. See also here for further details on how to control the number of digits in the output.
-
...
+
...
additional arguments.
Details
-
+
Specifying the Data
@@ -206,9 +207,7 @@
Observed Ef
Value
-
-
-
An object of class c("rma.mh","rma"). The object is a list containing the following components:
+
An object of class c("rma.mh","rma"). The object is a list containing the following components:
Meta-Analysis via Multivariate/Multilevel Linear (Mixed-Effects) Models
-
+
rma.mv.Rd
@@ -104,94 +104,95 @@
Meta-Analysis via Multivariate/Multilevel Linear (Mixed-Effects) Models
Arguments
-
yi
+
+
yi
vector of length \(k\) with the observed effect sizes or outcomes. See ‘Details’.
-
V
+
V
vector of length \(k\) with the corresponding sampling variances or a \(k \times k\) variance-covariance matrix of the sampling errors. See ‘Details’.
-
W
+
W
optional argument to specify a vector of length \(k\) with user-defined weights or a \(k \times k\) user-defined weight matrix. See ‘Details’.
-
mods
+
mods
optional argument to include one or more moderators in the model. A single moderator can be given as a vector of length \(k\) specifying the values of the moderator. Multiple moderators are specified by giving a matrix with \(k\) rows and as many columns as there are moderator variables. Alternatively, a model formula can be used to specify the model. See ‘Details’.
-
random
+
random
either a single one-sided formula or list of one-sided formulas to specify the random-effects structure of the model. See ‘Details’.
-
struct
+
struct
character string to specify the variance structure of an ~ inner | outer formula in the random argument. Either "CS" for compound symmetry, "HCS" for heteroscedastic compound symmetry, "UN" or "GEN" for an unstructured variance-covariance matrix, "ID" for a scaled identity matrix, "DIAG" for a diagonal matrix, "AR" for an AR(1) autoregressive structure, "HAR" for a heteroscedastic AR(1) autoregressive structure, "CAR" for a continuous-time autoregressive structure, or one of "SPEXP", "SPGAU", "SPLIN", "SPRAT", or "SPSPH" for one of the spatial correlation structures. See ‘Details’.
-
intercept
+
intercept
logical to specify whether an intercept should be added to the model (the default is TRUE). Ignored when mods is a formula.
-
data
+
data
optional data frame containing the data supplied to the function.
-
slab
+
slab
optional vector with labels for the \(k\) outcomes/studies.
-
subset
+
subset
optional (logical or numeric) vector to specify the subset of studies (or more precisely, rows of the dataset) that should be used for the analysis.
-
method
+
method
character string to specify whether the model should be fitted via maximum likelihood ("ML") or via restricted maximum likelihood ("REML") estimation (the default is "REML").
-
test
+
test
character string to specify how test statistics and confidence intervals for the fixed effects should be computed. By default (test="z"), Wald-type tests and CIs are obtained, which are based on a standard normal distribution. When test="t", a t-distribution is used instead. See ‘Details’ and also here for some recommended practices.
-
dfs
+
dfs
character string to specify how the (denominator) degrees of freedom should be calculated when test="t". Either dfs="residual" or dfs="contain". Can also be a numeric vector with the degrees of freedom for each model coefficient. See ‘Details’.
-
level
+
level
numeric value between 0 and 100 to specify the confidence interval level (the default is 95; see here for details).
-
btt
+
btt
optional vector of indices to specify which coefficients to include in the omnibus test of moderators. Can also be a string to grep for. See ‘Details’.
-
R
+
R
an optional named list of known correlation matrices corresponding to (some of) the components specified via the random argument. See ‘Details’.
-
Rscale
+
Rscale
character string, integer, or logical to specify how matrices specified via the R argument should be scaled. See ‘Details’.
-
sigma2
+
sigma2
optional numeric vector (of the same length as the number of random intercept components specified via the random argument) to fix the corresponding \(\sigma^2\) value(s). A specific \(\sigma^2\) value can be fixed by setting the corresponding element of this argument to the desired value. A specific \(\sigma^2\) value will be estimated if the corresponding element is set equal to NA. See ‘Details’.
-
tau2
+
tau2
optional numeric value (for struct="CS", "AR", "CAR", or a spatial correlation structure) or vector (for struct="HCS", "UN", or "HAR") to fix the amount of (residual) heterogeneity for the levels of the inner factor corresponding to an ~ inner | outer formula specified in the random argument. A numeric value fixes a particular \(\tau^2\) value, while NA means that the value should be estimated. See ‘Details’.
-
rho
+
rho
optional numeric value (for struct="CS", "HCS", "AR", "HAR", "CAR", or a spatial correlation structure) or vector (for struct="UN") to fix the correlation between the levels of the inner factor corresponding to an ~ inner | outer formula specified in the random argument. A numeric value fixes a particular \(\rho\) value, while NA means that the value should be estimated. See ‘Details’.
-
gamma2
+
gamma2
as tau2 argument, but for a second ~ inner | outer formula specified in the random argument. See ‘Details’.
-
phi
+
phi
as rho argument, but for a second ~ inner | outer formula specified in the random argument. See ‘Details’.
-
cvvc
+
cvvc
logical to specify whether to calculate the variance-covariance matrix of the variance/correlation component estimates (can also be set to "varcov" or "varcor"). See ‘Details’.
-
sparse
+
sparse
logical to specify whether the function should use sparse matrix objects to the extent possible (can speed up model fitting substantially for certain models). See ‘Note’.
-
verbose
+
verbose
logical to specify whether output should be generated on the progress of the model fitting (the default is FALSE). Can also be an integer. Values > 1 generate more verbose output. See ‘Note’.
-
digits
+
digits
optional integer to specify the number of decimal places to which the printed results should be rounded. If unspecified, the default is 4. See also here for further details on how to control the number of digits in the output.
-
control
+
control
optional list of control values for the estimation algorithms. If unspecified, default values are defined inside the function. See ‘Note’.
-
...
+
...
additional arguments.
Details
-
+
Specifying the Data
@@ -308,9 +309,7 @@
Var-Cov
Value
-
-
-
An object of class c("rma.mv","rma"). The object is a list containing the following components:
+
An object of class c("rma.mv","rma"). The object is a list containing the following components:
vector with the \(2 \times 2\) table frequencies (upper left cell). See below and the documentation of the escalc function for more details.
-
bi
+
bi
vector with the \(2 \times 2\) table frequencies (upper right cell). See below and the documentation of the escalc function for more details.
-
ci
+
ci
vector with the \(2 \times 2\) table frequencies (lower left cell). See below and the documentation of the escalc function for more details.
-
di
+
di
vector with the \(2 \times 2\) table frequencies (lower right cell). See below and the documentation of the escalc function for more details.
-
n1i
+
n1i
vector with the group sizes or row totals (first group). See below and the documentation of the escalc function for more details.
-
n2i
+
n2i
vector with the group sizes or row totals (second group). See below and the documentation of the escalc function for more details.
-
data
+
data
optional data frame containing the data supplied to the function.
-
slab
+
slab
optional vector with labels for the \(k\) studies.
-
subset
+
subset
optional (logical or numeric) vector to specify the subset of studies that should be used for the analysis.
-
add
+
add
non-negative number to specify the amount to add to zero cells when calculating the observed effect sizes of the individual studies. Can also be a vector of two numbers, where the first number is used in the calculation of the observed effect sizes and the second number is used when applying Peto's method. See below and the documentation of the escalc function for more details.
-
to
+
to
character string to specify when the values under add should be added (either "only0", "all", "if0all", or "none"). Can also be a character vector, where the first string again applies when calculating the observed effect sizes or outcomes and the second string when applying Peto's method. See below and the documentation of the escalc function for more details.
-
drop00
+
drop00
logical to specify whether studies with no cases (or only cases) in both groups should be dropped when calculating the observed effect sizes or outcomes (the outcomes for such studies are set to NA). Can also be a vector of two logicals, where the first applies to the calculation of the observed effect sizes or outcomes and the second when applying Peto's method. See below and the documentation of the escalc function for more details.
-
level
+
level
numeric value between 0 and 100 to specify the confidence interval level (the default is 95; see here for details).
-
verbose
+
verbose
logical to specify whether output should be generated on the progress of the model fitting (the default is FALSE).
-
digits
+
digits
optional integer to specify the number of decimal places to which the printed results should be rounded. If unspecified, the default is 4. See also here for further details on how to control the number of digits in the output.
-
...
+
...
additional arguments.
Details
-
+
Specifying the Data
@@ -186,9 +187,7 @@
Observed Ef
Value
-
-
-
An object of class c("rma.peto","rma"). The object is a list containing the following components:
+
An object of class c("rma.peto","rma"). The object is a list containing the following components:
vector of length \(k\) with the observed effect sizes or outcomes. See ‘Details’.
-
vi
+
vi
vector of length \(k\) with the corresponding sampling variances. See ‘Details’.
-
sei
+
sei
vector of length \(k\) with the corresponding standard errors (only relevant when not using vi). See ‘Details’.
-
weights
+
weights
optional argument to specify a vector of length \(k\) with user-defined weights. See ‘Details’.
-
ai
+
ai
see below and the documentation of the escalc function for more details.
-
bi
+
bi
see below and the documentation of the escalc function for more details.
-
ci
+
ci
see below and the documentation of the escalc function for more details.
-
di
+
di
see below and the documentation of the escalc function for more details.
-
n1i
+
n1i
see below and the documentation of the escalc function for more details.
-
n2i
+
n2i
see below and the documentation of the escalc function for more details.
-
x1i
+
x1i
see below and the documentation of the escalc function for more details.
-
x2i
+
x2i
see below and the documentation of the escalc function for more details.
-
t1i
+
t1i
see below and the documentation of the escalc function for more details.
-
t2i
+
t2i
see below and the documentation of the escalc function for more details.
-
m1i
+
m1i
see below and the documentation of the escalc function for more details.
-
m2i
+
m2i
see below and the documentation of the escalc function for more details.
-
sd1i
+
sd1i
see below and the documentation of the escalc function for more details.
-
sd2i
+
sd2i
see below and the documentation of the escalc function for more details.
-
xi
+
xi
see below and the documentation of the escalc function for more details.
-
mi
+
mi
see below and the documentation of the escalc function for more details.
-
ri
+
ri
see below and the documentation of the escalc function for more details.
-
ti
+
ti
see below and the documentation of the escalc function for more details.
-
fi
+
fi
see below and the documentation of the escalc function for more details.
-
pi
+
pi
see below and the documentation of the escalc function for more details.
-
sdi
+
sdi
see below and the documentation of the escalc function for more details.
-
r2i
+
r2i
see below and the documentation of the escalc function for more details.
-
ni
+
ni
see below and the documentation of the escalc function for more details.
-
mods
+
mods
optional argument to include one or more moderators in the model. A single moderator can be given as a vector of length \(k\) specifying the values of the moderator. Multiple moderators are specified by giving a matrix with \(k\) rows and as many columns as there are moderator variables. Alternatively, a model formula can be used to specify the model. See ‘Details’.
-
scale
+
scale
optional argument to include one or more predictors for the scale part in a location-scale model. See ‘Details’.
-
measure
+
measure
character string to specify the type of data supplied to the function. When measure="GEN" (default), the observed effect sizes or outcomes and corresponding sampling variances should be supplied to the function via the yi and vi arguments, respectively (instead of the sampling variances, one can supply the standard errors via the sei argument). Alternatively, one can set measure to one of the effect sizes or outcome measures described under the documentation for the escalc function in which case one must specify the required data via the appropriate arguments (see escalc).
-
intercept
+
intercept
logical to specify whether an intercept should be added to the model (the default is TRUE). Ignored when mods is a formula.
-
data
+
data
optional data frame containing the data supplied to the function.
-
slab
+
slab
optional vector with labels for the \(k\) studies.
-
subset
+
subset
optional (logical or numeric) vector to specify the subset of studies that should be used for the analysis.
character string to specify whether an equal- or a random-effects model should be fitted. An equal-effects model is fitted when using method="EE". A random-effects model is fitted by setting method equal to one of the following: "DL", "HE", "HS", "HSk", "SJ", "ML", "REML", "EB", "PM", "GENQ", "PMM", or "GENQM". The default is "REML". See ‘Details’.
-
weighted
+
weighted
logical to specify whether weighted (default) or unweighted estimation should be used to fit the model (the default is TRUE).
-
test
+
test
character string to specify how test statistics and confidence intervals for the fixed effects should be computed. By default (test="z"), Wald-type tests and CIs are obtained, which are based on a standard normal distribution. When test="t", a t-distribution is used instead. When test="knha", the method by Knapp and Hartung (2003) is used. See ‘Details’ and also here for some recommended practices.
-
level
+
level
numeric value between 0 and 100 to specify the confidence interval level (the default is 95; see here for details).
-
btt
+
btt
optional vector of indices to specify which coefficients to include in the omnibus test of moderators. Can also be a string to grep for. See ‘Details’.
-
att
+
att
optional vector of indices to specify which scale coefficients to include in the omnibus test. Only relevant for location-scale models. See ‘Details’.
-
tau2
+
tau2
optional numeric value to specify the amount of (residual) heterogeneity in a random- or mixed-effects model (instead of estimating it). Useful for sensitivity analyses (e.g., for plotting results as a function of \(\tau^2\)). If unspecified, the value of \(\tau^2\) is estimated from the data.
-
verbose
+
verbose
logical to specify whether output should be generated on the progress of the model fitting (the default is FALSE). Can also be an integer. Values > 1 generate more verbose output. See ‘Note’.
-
digits
+
digits
optional integer to specify the number of decimal places to which the printed results should be rounded. If unspecified, the default is 4. See also here for further details on how to control the number of digits in the output.
-
control
+
control
optional list of control values for the iterative estimation algorithms. If unspecified, default values are defined inside the function. See ‘Note’.
Cluster-Robust Tests and Confidence Intervals for 'rma' Objects
-
+
robust.Rd
@@ -97,30 +97,31 @@
Cluster-Robust Tests and Confidence Intervals for 'rma' Objects
robust(x, cluster, ...)
-# S3 method for rma.uni
+# S3 method for class 'rma.uni'robust(x, cluster, adjust=TRUE, clubSandwich=FALSE, digits, ...)
-# S3 method for rma.mv
+# S3 method for class 'rma.mv'robust(x, cluster, adjust=TRUE, clubSandwich=FALSE, digits, ...)
Arguments
-
x
+
+
x
an object of class "rma.uni" or "rma.mv".
-
cluster
+
cluster
vector to specify the clustering variable to use for constructing the sandwich estimator of the variance-covariance matrix.
-
adjust
+
adjust
logical to specify whether a small-sample correction should be applied to the variance-covariance matrix.
-
clubSandwich
+
clubSandwich
logical to specify whether the clubSandwich package should be used to obtain the cluster-robust tests and confidence intervals.
-
digits
+
digits
optional integer to specify the number of decimal places to which the printed results should be rounded. If unspecified, the default is to take the value from the object.
-
...
+
...
other arguments.
@@ -133,9 +134,7 @@
Details
Value
-
-
-
An object of class "robust.rma". The object is a list containing the following components:
+
An object of class "robust.rma". The object is a list containing the following components:
beta
estimated coefficients of the model.
@@ -168,8 +167,6 @@
Value
The results are formatted and printed with the print.rma.uni and print.rma.mv functions (depending on the type of model).
-
-
Predicted/fitted values based on "robust.rma" objects can be obtained with the predict function. Tests for sets of model coefficients or linear combinations thereof can be obtained with the anova function.
selmodel(x, ...)
-# S3 method for rma.uni
+# S3 method for class 'rma.uni'selmodel(x, type, alternative="greater", prec, subset, delta,steps, decreasing=FALSE, verbose=FALSE, digits, control, ...)
Arguments
-
x
+
+
x
an object of class "rma.uni".
-
type
+
type
character string to specify the type of selection model. Possible options are "beta", "halfnorm", "negexp", "logistic", "power", "negexppow", "stepfun", "trunc", and "truncest". Can be abbreviated.
-
alternative
+
alternative
character string to specify the sidedness of the hypothesis when testing the observed outcomes. Possible options are "greater" (the default), "less", or "two.sided". Can be abbreviated.
-
prec
+
prec
optional character string to specify the measure of precision (only relevant for selection models that can incorporate this into the selection function). Possible options are "sei", "vi", "ninv", or "sqrtninv".
-
subset
+
subset
optional (logical or numeric) vector to specify the subset of studies to which the selection function applies.
-
delta
+
delta
optional numeric vector (of the same length as the number of selection model parameters) to fix the corresponding \(\delta\) value(s). A \(\delta\) value can be fixed by setting the corresponding element of this argument to the desired value. A \(\delta\) value will be estimated if the corresponding element is set equal to NA.
-
steps
+
steps
numeric vector of one or more values that can or must be specified for certain selection functions.
-
decreasing
+
decreasing
logical to specify whether the \(\delta\) values in a step function selection model must be a monotonically decreasing function of the p-values (the default is FALSE). Only relevant when type="stepfun".
-
verbose
+
verbose
logical to specify whether output should be generated on the progress of the model fitting (the default is FALSE). Can also be an integer. Values > 1 generate more verbose output. See ‘Note’.
-
digits
+
digits
optional integer to specify the number of decimal places to which the printed results should be rounded. If unspecified, the default is to take the value from the object.
-
control
+
control
optional list of control values for the estimation algorithm. See ‘Note’.
-
...
+
...
other arguments.
@@ -235,9 +236,7 @@
Subsets
Value
-
-
-
An object of class c("rma.uni","rma"). The object is a list containing the same components as a regular c("rma.uni","rma") object, but the parameter estimates are based on the selection model. Most importantly, the following elements are modified based on the selection model:
+
An object of class c("rma.uni","rma"). The object is a list containing the same components as a regular c("rma.uni","rma") object, but the parameter estimates are based on the selection model. Most importantly, the following elements are modified based on the selection model:
# S3 method for class 'rma'simulate(object, nsim=1, seed=NULL, olim, ...)
Arguments
-
object
+
+
object
an object of class "rma".
-
nsim
+
nsim
number of response vectors to simulate (defaults to 1).
-
seed
+
seed
an object to specify if and how the random number generator should be initialized (‘seeded’). Either NULL or an integer that will be used in a call to set.seed before simulating the response vectors. If set, the value is saved as the "seed" attribute of the returned value. The default, NULL will not change the random generator state, and return .Random.seed as the "seed" attribute; see ‘Value’.
-
olim
+
olim
optional argument to specify observation/outcome limits for the simulated values. If unspecified, no limits are used.
-
...
+
...
other arguments.
@@ -123,11 +124,7 @@
Details
Value
-
-
-
A data frame with nsim columns with the simulated effect sizes or outcomes.
-
-
+
A data frame with nsim columns with the simulated effect sizes or outcomes.
The data frame comes with an attribute "seed". If argument seed is NULL, the attribute is the value of .Random.seed before the simulation was started; otherwise it is the value of the seed argument with a "kind" attribute with value as.list(RNGkind()).
tes(x, vi, sei, subset, data, H0=0, alternative="two.sided", alpha=.05, theta, tau2,test, tes.alternative="greater", progbar=TRUE, tes.alpha=.10, digits, ...)
-# S3 method for tes
+# S3 method for class 'tes'print(x, digits=x$digits, ...)
Arguments
-
-
These arguments pertain to data input:
-
x
+
These arguments pertain to data input:
+
+
x
a vector with the observed effect sizes or outcomes or an object of class "rma".
-
vi
+
vi
vector with the corresponding sampling variances (ignored if x is an object of class "rma").
-
sei
+
sei
vector with the corresponding standard errors (note: only one of the two, vi or sei, needs to be specified).
-
subset
+
subset
optional (logical or numeric) vector to specify the subset of studies that should be included (ignored if x is an object of class "rma").
-
data
+
data
optional data frame containing the variables given to the arguments above.
These arguments pertain to the tests of the observed effect sizes or outcomes:
-
H0
+
+
H0
numeric value to specify the value of the effect size or outcome under the null hypothesis (the default is 0).
-
alternative
+
alternative
character string to specify the sidedness of the hypothesis when testing the observed effect sizes or outcomes. Possible options are "two.sided" (the default), "greater", or "less". Can be abbreviated.
-
alpha
+
alpha
alpha level for testing the observed effect sizes or outcomes (the default is .05).
These arguments pertain to the power of the tests:
-
theta
+
+
theta
optional numeric value to specify the value of the true effect size or outcome under the alternative hypothesis. If unspecified, it will be estimated based on the data or the value is taken from the "rma" object.
-
tau2
+
tau2
optional numeric value to specify the amount of heterogeneity in the true effect sizes or outcomes. If unspecified, the true effect sizes or outcomes are assumed to be homogeneous or the value is taken from the "rma" object.
These arguments pertain to the test of excess significance:
-
test
+
+
test
optional character string to specify the type of test to use for conducting the test of excess significance. Possible options are "chi2", "binom", or "exact". Can be abbreviated. If unspecified, the function chooses the type of test based on the data.
-
tes.alternative
+
tes.alternative
character string to specify the sidedness of the hypothesis for the test of excess significance. Possible options are "greater" (the default), "two.sided", or "less". Can be abbreviated.
-
progbar
+
progbar
logical to specify whether a progress bar should be shown (the default is TRUE). Only relevant when conducting an exact test.
-
tes.alpha
+
tes.alpha
alpha level for the test of excess significance (the default is .10). Only relevant for finding the ‘limit estimate’.
Miscellaneous arguments:
-
digits
+
+
digits
optional integer to specify the number of decimal places to which the printed results should be rounded.
-
...
+
...
other arguments.
@@ -174,9 +178,7 @@
Details
Value
-
-
-
An object of class "tes". The object is a list containing the following components:
+
An object of class "tes". The object is a list containing the following components:
a character string to specify the effect size or outcome measure corresponding to the summary data supplied. See ‘Details’ and the documentation of the escalc function for possible options.
-
ai
+
ai
vector with the \(2 \times 2\) table frequencies (upper left cell).
-
bi
+
bi
vector with the \(2 \times 2\) table frequencies (upper right cell).
-
ci
+
ci
vector with the \(2 \times 2\) table frequencies (lower left cell).
-
di
+
di
vector with the \(2 \times 2\) table frequencies (lower right cell).
-
n1i
+
n1i
vector with the group sizes or row totals (first group/row).
-
n2i
+
n2i
vector with the group sizes or row totals (second group/row).
-
x1i
+
x1i
vector with the number of events (first group).
-
x2i
+
x2i
vector with the number of events (second group).
-
t1i
+
t1i
vector with the total person-times (first group).
-
t2i
+
t2i
vector with the total person-times (second group).
-
m1i
+
m1i
vector with the means (first group or time point).
-
m2i
+
m2i
vector with the means (second group or time point).
-
sd1i
+
sd1i
vector with the standard deviations (first group or time point).
-
sd2i
+
sd2i
vector with the standard deviations (second group or time point).
-
xi
+
xi
vector with the frequencies of the event of interest.
-
mi
+
mi
vector with the frequencies of the complement of the event of interest or the group means.
-
ri
+
ri
vector with the raw correlation coefficients.
-
ti
+
ti
vector with the total person-times.
-
sdi
+
sdi
vector with the standard deviations.
-
ni
+
ni
vector with the sample/group sizes.
-
data
+
data
optional data frame containing the variables given to the arguments above.
-
slab
+
slab
optional vector with labels for the studies.
-
subset
+
subset
optional (logical or numeric) vector to specify the subset of studies that should included in the data frame returned by the function.
optional logical whether a very long format should be used (only relevant for \(2 \times 2\) or \(1 \times 2\) table data).
-
append
+
append
logical to specify whether the data frame specified via the data argument (if one has been specified) should be returned together with the long format data (the default is TRUE). Can also be a character or numeric vector to specify which variables from data to append.
-
var.names
+
var.names
optional character vector with variable names (the length depends on the data type). If unspecified, the function sets appropriate variable names by default.
@@ -204,9 +205,7 @@
Details
Value
-
-
-
A data frame with either \(k\), \(2 \times k\), or \(4 \times k\) rows and an appropriate number of columns (depending on the data type) with the data in long format. If append=TRUE and a data frame was specified via the data argument, then the data in long format are appended to the original data frame (with rows repeated an appropriate number of times).
+
A data frame with either \(k\), \(2 \times k\), or \(4 \times k\) rows and an appropriate number of columns (depending on the data type) with the data in long format. If append=TRUE and a data frame was specified via the data argument, then the data in long format are appended to the original data frame (with rows repeated an appropriate number of times).
a character string to specify the effect size or outcome measure corresponding to the summary data supplied. See ‘Details’ and the documentation of the escalc function for possible options.
-
ai
+
ai
vector with the \(2 \times 2\) table frequencies (upper left cell).
-
bi
+
bi
vector with the \(2 \times 2\) table frequencies (upper right cell).
-
ci
+
ci
vector with the \(2 \times 2\) table frequencies (lower left cell).
-
di
+
di
vector with the \(2 \times 2\) table frequencies (lower right cell).
-
n1i
+
n1i
vector with the group sizes or row totals (first group/row).
-
n2i
+
n2i
vector with the group sizes or row totals (second group/row).
-
x1i
+
x1i
vector with the number of events (first group).
-
x2i
+
x2i
vector with the number of events (second group).
-
t1i
+
t1i
vector with the total person-times (first group).
-
t2i
+
t2i
vector with the total person-times (second group).
-
m1i
+
m1i
vector with the means (first group or time point).
-
m2i
+
m2i
vector with the means (second group or time point).
-
sd1i
+
sd1i
vector with the standard deviations (first group or time point).
-
sd2i
+
sd2i
vector with the standard deviations (second group or time point).
-
xi
+
xi
vector with the frequencies of the event of interest.
-
mi
+
mi
vector with the frequencies of the complement of the event of interest or the group means.
-
ri
+
ri
vector with the raw correlation coefficients.
-
ti
+
ti
vector with the total person-times.
-
sdi
+
sdi
vector with the standard deviations.
-
ni
+
ni
vector with the sample/group sizes.
-
data
+
data
optional data frame containing the variables given to the arguments above.
-
slab
+
slab
optional vector with labels for the studies.
-
subset
+
subset
optional (logical or numeric) vector to specify the subset of studies that should be included in the array returned by the function.
either the name (given as a character string) or the position (given as a single number) of the study variable in the data frame.
-
grp
+
grp
either the name (given as a character string) or the position (given as a single number) of the group variable in the data frame.
-
ref
+
ref
optional character string to specify the reference group (must be one of the groups in the group variable). If not given, the most frequently occurring group is used as the reference group.
-
grpvars
+
grpvars
either the names (given as a character vector) or the positions (given as a numeric vector) of the group-level variables.
-
postfix
+
postfix
a character string of length 2 giving the affix that is placed after the names of the group-level variables for the first and second group.
-
addid
+
addid
logical to specify whether a row id variable should be added to the data frame (the default is TRUE).
-
addcomp
+
addcomp
logical to specify whether a comparison id variable should be added to the data frame (the default is TRUE).
-
adddesign
+
adddesign
logical to specify whether a design id variable should be added to the data frame (the default is TRUE).
-
minlen
+
minlen
integer to specify the minimum length of the shortened group names for the comparison and design id variables (the default is 2).
-
var.names
+
var.names
character vector with three elements to specify the name of the id, comparison, and design variables (the defaults are "id", "comp", and "design", respectively).
@@ -148,9 +149,7 @@
Details
Value
-
-
-
A data frame with rows contrasting groups against a reference group and an appropriate number of columns (depending on the number of group-level outcome variables).
+
A data frame with rows contrasting groups against a reference group and an appropriate number of columns (depending on the number of group-level outcome variables).
trimfill(x, ...)
-# S3 method for rma.uni
+# S3 method for class 'rma.uni'trimfill(x, side, estimator="L0", maxiter=100, verbose=FALSE, ilim, ...)
Arguments
-
x
+
+
x
an object of class "rma.uni".
-
side
+
side
optional character string (either "left" or "right") to specify on which side of the funnel plot the missing studies should be imputed. If left unspecified, the side is chosen within the function depending on the results of the regression test (see regtest for details on this test).
-
estimator
+
estimator
character string (either "L0", "R0", or "Q0") to specify the estimator for the number of missing studies (the default is "L0").
-
maxiter
+
maxiter
integer to specify the maximum number of iterations for the trim and fill method (the default is 100).
-
verbose
+
verbose
logical to specify whether output should be generated on the progress of the iterative algorithm used as part of the trim and fill method (the default is FALSE).
-
ilim
+
ilim
limits for the imputed values. If unspecified, no limits are used.
-
...
+
...
other arguments.
@@ -131,9 +132,7 @@
Details
Value
-
-
-
An object of class c("rma.uni.trimfill","rma.uni","rma"). The object is a list containing the same components as objects created by rma.uni, except that the data are augmented by the trim and fill method. The following components are also added:
+
An object of class c("rma.uni.trimfill","rma.uni","rma"). The object is a list containing the same components as objects created by rma.uni, except that the data are augmented by the trim and fill method. The following components are also added:
Construct or Approximate the Variance-Covariance Matrix of Dependent Effect Sizes or Outcomes
-
+
vcalc.Rd
@@ -101,61 +101,62 @@
Construct or Approximate the Variance-Covariance Matrix of Dependent Effect
Arguments
-
vi
+
+
vi
numeric vector to specify the sampling variances of the observed effect sizes or outcomes.
-
cluster
+
cluster
vector to specify the clustering variable (e.g., study).
-
subgroup
+
subgroup
optional vector to specify different (independent) subgroups within clusters.
-
obs
+
obs
optional vector to distinguish different observed effect sizes or outcomes corresponding to the same construct or response/dependent variable.
-
type
+
type
optional vector to distinguish different types of constructs or response/dependent variables underlying the observed effect sizes or outcomes.
-
time1
+
time1
optional numeric vector to specify the time points when the observed effect sizes or outcomes were obtained (in the first condition if the observed effect sizes or outcomes represent contrasts between two conditions).
-
time2
+
time2
optional numeric vector to specify the time points when the observed effect sizes or outcomes were obtained in the second condition (only relevant when the observed effect sizes or outcomes represent contrasts between two conditions).
-
grp1
+
grp1
optional vector to specify the group of the first condition when the observed effect sizes or outcomes represent contrasts between two conditions.
-
grp2
+
grp2
optional vector to specify the group of the second condition when the observed effect sizes or outcomes represent contrasts between two conditions.
-
w1
+
w1
optional numeric vector to specify the size of the group (or more generally, the inverse-sampling variance weight) of the first condition when the observed effect sizes or outcomes represent contrasts between two conditions.
-
w2
+
w2
optional numeric vector to specify the size of the group (or more generally, the inverse-sampling variance weight) of the second condition when the observed effect sizes or outcomes represent contrasts between two conditions.
-
data
+
data
optional data frame containing the variables given to the arguments above.
-
rho
+
rho
argument to specify the correlation(s) of observed effect sizes or outcomes measured concurrently. See ‘Details’.
-
phi
+
phi
argument to specify the autocorrelation of observed effect sizes or outcomes measured at different time points. See ‘Details’.
-
rvars
+
rvars
optional argument for specifying the variables that correspond to the correlation matrices of the studies (if this is specified, all arguments above except for cluster and subgroup are ignored). See ‘Details’.
-
checkpd
+
checkpd
logical to specify whether to check that the variance-covariance matrices within clusters are positive definite (the default is TRUE). See ‘Note’.
-
nearpd
+
nearpd
logical to specify whether the nearPD function from the Matrix package should be used on variance-covariance matrices that are not positive definite. See ‘Note’.
-
sparse
+
sparse
logical to specify whether the variance-covariance matrix should be returned as a sparse matrix (the default is FALSE).
Extract Various Types of Variance-Covariance Matrices from 'rma' Objects
-
+
vcov.rma.Rd
@@ -95,19 +95,20 @@
Extract Various Types of Variance-Covariance Matrices from 'rma' Objects
-
# S3 method for rma
+
# S3 method for class 'rma'vcov(object, type="fixed", ...)
Arguments
-
object
+
+
object
an object of class "rma".
-
type
+
type
character string to specify the type of variance-covariance matrix to return: type="fixed" returns the variance-covariance matrix of the fixed effects (the default), type="obs" returns the marginal variance-covariance matrix of the observed effect sizes or outcomes, type="fitted" returns the variance-covariance matrix of the fitted values, type="resid" returns the variance-covariance matrix of the residuals.
-
...
+
...
other arguments.
@@ -119,9 +120,7 @@
Details
Value
-
-
-
A matrix corresponding to the requested variance-covariance matrix.
+
A matrix corresponding to the requested variance-covariance matrix.
vif(x, ...)
-# S3 method for rma
+# S3 method for class 'rma'vif(x, btt, att, table=FALSE, reestimate=FALSE, sim=FALSE, progbar=TRUE, seed=NULL, parallel="no", ncpus=1, cl, digits, ...)
-# S3 method for vif.rma
+# S3 method for class 'vif.rma'print(x, digits=x$digits, ...)
Arguments
-
x
+
+
x
an object of class "rma" (for vif) or "vif.rma" (for print).
-
btt
+
btt
optional vector of indices (or list thereof) to specify a set of coefficients for which a generalized variance inflation factor (GVIF) should be computed. Can also be a string to grep for.
-
att
+
att
optional vector of indices (or list thereof) to specify a set of scale coefficients for which a generalized variance inflation factor (GVIF) should be computed. Can also be a string to grep for. Only relevant for location-scale models (see rma.uni).
-
table
+
table
logical to specify whether the VIFs should be added to the model coefficient table (the default is FALSE). Only relevant when btt (or att) is not specified.
-
reestimate
+
reestimate
logical to specify whether the model should be reestimated when removing moderator variables from the model for computing a (G)VIF (the default is FALSE).
-
sim
+
sim
logical to specify whether the distribution of each (G)VIF under independence should be simulated (the default is FALSE). Can also be an integer to specify how many values to simulate (when sim=TRUE, the default is 1000).
-
progbar
+
progbar
logical to specify whether a progress bar should be shown when sim=TRUE (the default is TRUE).
-
seed
+
seed
optional value to specify the seed of the random number generator when sim=TRUE (for reproducibility).
-
parallel
+
parallel
character string to specify whether parallel processing should be used (the default is "no"). For parallel processing, set to either "snow" or "multicore". See ‘Note’.
-
ncpus
+
ncpus
integer to specify the number of processes to use in the parallel processing.
-
cl
+
cl
optional cluster to use if parallel="snow". If unspecified, a cluster on the local machine is created for the duration of the call.
-
digits
+
digits
optional integer to specify the number of decimal places to which the printed results should be rounded. If unspecified, the default is to take the value from the object.
-
...
+
...
other arguments.
@@ -201,9 +202,7 @@
Simulating the
Value
-
-
-
An object of class "vif.rma". The object is a list containing the following components:
+
An object of class "vif.rma". The object is a list containing the following components:
vif
a list of data frames with the (G)VIFs and (G)SIFs and some additional information.
@@ -224,8 +223,6 @@
Value
When x was a location-scale model object and (G)VIFs can be computed for both the location and the scale coefficients, then the object is a list with elements beta and alpha, where each element is an "vif.rma" object as described above.
-
-
The results are formatted and printed with the print function. To format the results as a data frame, one can use the as.data.frame function. When sim=TRUE, the distribution of each (G)VIF can be plotted with the plot function.
# S3 method for class 'rma.uni'weights(object, type="diagonal", ...)
-# S3 method for rma.mh
+# S3 method for class 'rma.mh'weights(object, type="diagonal", ...)
-# S3 method for rma.peto
+# S3 method for class 'rma.peto'weights(object, type="diagonal", ...)
-# S3 method for rma.glmm
+# S3 method for class 'rma.glmm'weights(object, ...)
-# S3 method for rma.mv
+# S3 method for class 'rma.mv'weights(object, type="diagonal", ...)
Arguments
-
object
+
+
object
an object of class "rma.uni", "rma.mh", "rma.peto", or "rma.mv". The method is not yet implemented for objects of class "rma.glmm".
-
type
+
type
character string to specify whether to return only the diagonal of the weight matrix ("diagonal") or the entire weight matrix ("matrix"). For "rma.mv", this can also be "rowsum" for ‘row-sum weights’ (for intercept-only models).
-
...
+
...
other arguments.
Value
-
-
-
Either a vector with the diagonal elements of the weight matrix or the entire weight matrix. When only the diagonal elements are returned, they are given in % (and they add up to 100%).
-
-
+
Either a vector with the diagonal elements of the weight matrix or the entire weight matrix. When only the diagonal elements are returned, they are given in % (and they add up to 100%).
When the entire weight matrix is requested, this is always a diagonal matrix for objects of class "rma.uni", "rma.mh", "rma.peto".
-
-
For "rma.mv", the structure of the weight matrix depends on the model fitted (i.e., the random effects included and the variance-covariance matrix of the sampling errors) but is often more complex and not just diagonal.
-
-
For intercept-only "rma.mv" models, one can also take the sum over the rows in the weight matrix, which are actually the weights assigned to the observed effect sizes or outcomes when estimating the model intercept. These weights can be obtained with type="rowsum" (as with type="diagonal", they are also given in %). See here for a discussion of this.
