Jul 31, 2023 · Experimental design refers to how participants are allocated to different groups in an experiment. Types of design include repeated measures, independent groups, and matched pairs designs.

Repeated measures design is a research design that involves multiple measures of the same variable taken on the same or matched subjects either under different conditions or over two or more time periods. [1]

In this post, I’ll explain how repeated measures designs work along with their benefits and drawbacks. Additionally, I’ll work through a repeated measures ANOVA example to show you how to analyze this type of design and interpret the results. To learn more about ANOVA tests, read my ANOVA Overview.

A Repeated Measures Design is a research method that involves testing the same subjects under two or more conditions to analyze if there is a statistically significant difference among groups by partitioning variability into SS subjects and SS residual.

A study design with repeated measures data occurs when each experimental unit has multiple dependent variable observations collected at several time points. Often longitudinal data ( 1 , 2 ) are used interchangeably to describe repeated measures data.

For example, repeated measures designs are also known as repeated measures analysis of variance (ANOVA), repeated measures factors, or within-subjects designs. However, repeated measures may be performed within a multivariate ANOVA design as well.

We can analyse data using a repeated measures ANOVA for two types of study design. Studies that investigate either (1) changes in mean scores over three or more time points, or (2) differences in mean scores under three or more different conditions.