University of Michigan - Ann Arbor

Study 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.
Example: repeated measurements are collected in a longitudinal study in which change over time is assessed.

Repeated Measures Designs

James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An introduction to statistical learning (Vol. 112, pp. 3-7). New York: springer.

An Introduction to Statistical Learning with Applications in R

Repeated measures design reduces the effect of variability because the same subjects are used throughout the experiment. This allows the researcher to make powerful statistical conclusions with a relatively small set of subjects.

Why use repeated measures design?

1. More statistical power
2. Fewer subjects
3. Quicker and cheaper
4. Assess an effect over time

Benefits

Picture of a common crossover repeated measures design

An order effect is a primary disadvantage of within-subjects experimental designs. It occurs when participants' responses in various experimental conditions are systematically affected by the order in which they were exposed to those conditions. When order effects are not the direct focus of the research, they can act as problematic confounding variables that obscure the true effect of the independent variable.

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