The simulation results for each scenario are generated by the following R scripts. Running a script in batch mode from your system command line with, say,
R CMD BATCH --vanilla sim-omit.R
will create R output and simulation data files by the same name; sim-omit.Rout and sim-omit.RData, respectively.
File | Description |
---|---|
sim-omit.R | Averaging over an underlying moderator |
sim-stable.R | Weight stabilization |
sim-ar1.R | Non-independence working correlation structure |
Each of these scripts call routines defined in the files below.
File | Description |
---|---|
rsnmm.c | Data generator |
rsnmm.R | Data generator interface |
sim.R | Simulation routine |
init.R | Loads required packages and reads source files |
xgeepack.R | Extensions for the geepack R package; extract, from a geepack model object, elements (e.g. working covariance, estimating function) needed for variance calculations |
xzoo.R | Extensions for the zoo R package; apply lags, difference, rolling summaries to a sample of time series |
Instead of the application presented in the paper (which considers sensitive data), we provide an example using simulated data---both with and without use of the geepack R package. The zoo R package is used to easily define variables, but is not needed for estimation.
File | Description |
---|---|
example_geepack.R | Loads geepack and zoo extensions, generates data and runs an analysis similar to the application presented in the paper |
example_geepack.Rout | Provides the output obtained by running the example in batch mode |
example.R | Loads zoo extensions, generates data and runs an analysis similar to the application presented in the paper |
example.Rout | Provides the output obtained by running the example in batch mode |