Understanding Mixed-Effects Models Through Data Simulation

Experimental designs that sample both subjects and stimuli from a larger population need to account for random effects of using mixed-effects models. However, much this research is analyzed analysis variance on aggregated responses because researchers are not confident specifying interpreting This Tutorial explains how simulate data with random-effects structure analyze the linear regression (with lme4 R package), focus output in light simulated parameters. Data simulation only can enhance understanding these models work, but also enables perform power calculations complex designs. All materials associated article be accessed at https://osf.io/3cz2e/ .