What is the main goal of a repeated measures ANOVA?

The main goal of a repeated measures ANOVA is to assess differences within the same subjects. This statistical analysis is specifically designed to handle scenarios where the same subjects are measured under different conditions or at different times.

By using repeated measures, the analysis accounts for within-subject variability, which allows researchers to detect any changes over time or across conditions while controlling for individual differences. This is particularly valuable in psychology and other social sciences where individual responses can vary widely.

In a repeated measures design, each participant serves as their own control, which can improve the sensitivity of the test and reduce the error variance associated with individual differences. This focus on the same subjects allows researchers to more confidently interpret the effects of the treatments or time points being analyzed.

The other options do not capture the specific focus of repeated measures ANOVA. While comparing means across groups is the goal of independent measures ANOVA, and evaluating the impact of a single variable pertains more to bivariate tests like t-tests, they do not emphasize the repeated measures aspect. Similarly, analyzing the regression of multiple variables relates to regression analysis rather than ANOVA. Therefore, recognizing that repeated measures ANOVA focuses on within-subject variations is critical for understanding its purpose.