Repeated‐Measures Analysis of Variance

In a repeated-measures design (also called a within-participants design), every participant is exposed to each of the treatment conditions. The type of repeated-measures design and analysis discussed in this chapter is limited to the case in which only one independent variable is used. A repeated-measures analysis of variance (ANOVA) generates one F ratio; it tests for population mean differences among the levels of the independent variable. The repeated-measures ANOVA allows for the partitioning of the within-group variability into variance due to individual differences and variation due to experimental error. The chapter presents the formulas for the repeated-measures ANOVA and a worked problem illustrating the computational steps in the repeated-measures ANOVA. A rejected null hypothesis in a repeated-measures design that has more than two levels of the independent variable requires follow-up comparisons to locate the source(s) of the statistical evidence.