There are several methods available to analyze data that consists of repeated measurements taken on subjects or experimental units over time. These methods are designed to account for between subject variability and within subject variability. In this workshop we will cover the two most commonly used methods for analyzing repeated measures data: repeated measures ANOVA and mixed models. The assumptions, implementation, and interpretation of each method will be discussed. We will also discuss how repeated measures ANOVA and mixed models compare in terms of the flexibility of their assumptions regarding the structure of the within subject variability.