Includes data manipulation, checking test assumptions, fitting a mixed-effects model, evaluating general linear hypotheses, generating and comparing control data, false discovery rate (FDR) and false coverage-statement rate (FCR) corrections, and data visualization. Within- and between-participant comparisons are made.
This script utilizes a single outcome variable measured at multiple timepoints, but contains everything needed to be applied to multiple variables. Most of its contents can be modified easily to construct a batch processing pipeline.
suddengains, reshape2, dplyr, lme4, ggplot2, glmmTMB, sjPlot, MASS, lattice, cowplot, ggpubr, multcomp, viridis
Beyond R, no downloads are required before starting. All downloads—including retrieving sample data—occur within the R script.
Tested on a Mac running OS Monterey 12.1 using R version 4.2.0. All packages are hosted on CRAN and are expected to be compatible with a variety of operating systems.