In this post, you will learn how to set up a random intercept model in R. This model is useful for analyzing data from experiments that involve repeated measurements of the same participants or items. It lets you control for variability in the outcome variable due to random effects, such as individual differences or item difficulty, while estimating the fixed effects of your predictors of interest. In this blog post, you will also learn how to use R to visualize a random intercept model.
Outline
More specifically, in this tutorial, you will learn:
- Installing and loading the necessary packages and preparing your data are prerequisites for running a random intercept model in R.
- How to carry out a random intercept model in R using the
lmer()function from the lme4 package and interpret the output from the lmerTest package. - How to visualize a random intercept model in R using the
plot_model()function from the sjPlot package, and how to customize the plots to suit your needs.