R functions for data processing and data analysis

This repository includes a set of R functions for self-report, physiological, and behavioural data management and data analysis, and especially for dealing with multilevel data.

R functions

Data management

• checklist_sep splits multiple-choice checklist variable into multiple columns.

Descriptives

• itemsICC computes and prints the intraclass correlation coefficient for one or more time-varying variables.

• multidesc computes and prints descriptive statistics (mean and SD) and intraclass correlation of a multilevel dataset.

• multicorr computes the correlation matrix of a multilevel dataset.

Psychometrics

• fit.ind computes and prints fit indices from mono- and multi-level confirmatory factor analysis models.

• MCFArel computes and prints composite reliability index (Chronbach's alpha and McDondald's omega) from a multilevel confirmatory factor analysis model.

• GTHEORYrel computes and prints variance components and reliability indices from a multilevel dataset, as described by Cranford, J. A., Shrout, P. E., Iida, M., Rafaeli, E., Yip, T., & Bolger, N. (2006). A Procedure for Evaluating Sensitivity to Within-Person Change: Can Mood Measures in Diary Studies Detect Change Reliably? Personality and Social Psychology Bulletin, 32(7), 917–929. https://doi.org/10.1177/0146167206287721

Multilevel modeling

• glmerAn fits generalized linear (mixed-effects) regression models and prints core numerical and graphical ouputs.

• key.resPlot visualizes the key results (i.e., Akaike weight, likelihood ratio test, and t value) obtained with the glmerAn function.

Influential analysis

• sample.fluct recoursively compute and save parameter estimates from multilevel CFA estimates by removing participants one-to-one.

• plot.infl visualizes the results of the sample.fluct function.

R packages

The functions are based on the following R packages:

• car

• ggplot2

• Hmisc

• knitr

• lavaan

• lme4

• ordinal

• MuMIn

• Rmisc

• sjPlot

• tcltk

• XML