Google

Measuring the dependent variable multiple times for each participant in a within-subjects design allows for a more refined calculation of within-groups variance ($$MS_W$$). Because stable individual differences can be quantified and subtracted from $$MS_W$$, the resulting denominator in the $$F$$-ratio is smaller. This lower $$MS_W$$ leads to a higher $$F$$-value, making the repeated-measures ANOVA a more sensitive statistical test.

Within-Groups Variance in Repeated-Measures ANOVA

If a study uses reaction time as a dependent variable, stable individual differences (such as variations in participants' nervous systems and muscles) will naturally cause some individuals to be faster or slower. In a between-subjects ANOVA, these differences add to the within-groups variance ($$MS_W$$), decreasing the $$F$$-ratio. In a repeated-measures ANOVA, these differences are measured and subtracted from $$MS_W$$, increasing the test's sensitivity.

Example of Individual Differences in ANOVA

In a repeated-measures ANOVA, how is the within-groups variance affected by measuring the dependent variable multiple times for each participant?

Arrange the steps that explain why measuring participants multiple times increases the sensitivity of a statistical test by refining the within-groups variance ($$MS_W$$).

Learn Before

Related