Introduction to Linear Mixed Effects Models

Reuben Thomas Associate Core Director

More often than not, biological experiments involve repeated measures. Examples include responses measured in cellular assays, where the repeated measures may occur over multiple experimental batches, multiple plates, or multiple wells within a plate. Observations of mouse behavior over consecutive trials would be another example of experiments involving repeated measures.

The distinctions between biological and technical replicates become less clear in these scenarios. Standard statistical tests like t-tests and ANOVA are not applicable. Instead, analysis of such data requires more sophisticated approaches, such as linear mixed effects modeling.

In this course, you will learn the motivation for the use of these models, the underlying description and assumptions behind them, example scenarios where they can be used, and code to implement and interpret these models in R.

Visit the workshop site for more details and materials.