Analysis and visualization of free recall data.
psifrr relies on the
Psifr Python
package, which is called from R using the reticulate package.
First, install remotes:
install.packages("remotes")Next, install psifrr with:
remotes::install_github("mortonne/psifrr")To calculate a serial position curve for each participant in a sample dataset:
library(psifrr)
raw <- sample_data("Morton2013")
data <- merge_free_recall(raw)
recall <- spc(data)See the psifrr website for full documentation and a list of available analyses.
Generally the best way to get your data into shape for analysis in psifrr is to create a CSV (or TSV) file with one row for each event in the experiment, including study events (i.e., item presentations) and all recall attempts (including repeats and intrusions). See importing data for details.
If you use psifrr, please cite the Psifr paper:
Morton, N. W., (2020). Psifr: Analysis and visualization of free recall data. Journal of Open Source Software, 5(54), 2669, https://doi.org/10.21105/joss.02669