Solved – Power Analysis for repeated measures ANOVA

repeated measuresstatistical-power

I am trying to run a post-hoc power analysis on a previously published report. The intent is to calculate the average obtained power for (the equivalent of) Cohen's effects of d = .20, .50, .80) for all main effects and contrasts.

The study design is as follows: N = 240, repeated measures mixed (split-plot) 2×4(x4) ANOVA. To simplify, the first two factors are between-subjects. Factor A (gender) has 2 levels (male, female obviously), Factor B (ethnicity) has 4 levels totalling 8 experimental groups. Groups are balanced with n = 30 at the smallest unit of observation. Each of the 8 groups performs the same task under 4 different conditions. No information about the degree to which the responses are correlated is given. Pretty straightforward. Hopefully I haven't left anything out.

I can use STATA, GPower, or other online sources to calculate power for one and two way repeated measures ANOVA, but I haven't found a way to do this particular design.

Has anyone had any luck configuring either R, STATA syntax, or done some other voodoo to calculate power for this design?

Best Answer

To calculate the effect size for a 2-way repeated ANOVA on both factors, you can use two formulas:

$$\eta^2_{partial} =\frac{SS} {SS+SS_{Error}}$$ where $SS$ is the sum of squares.

The number you'll get, must then be multiplied with 100, so you'll have the percentage of explained influence of the factor on your dependent variable.

The other way to do this, is with the formulas:

$f^2 = F \cdot \frac{ df}{df_{error}} \rightarrow \eta^2_{partial} = \frac{f^2} {1+f^2}$

Likewise you'll have to multiple your result with 100, so you'll get the explained variance.

Both these formulas tell you about the effect size for your sample, but not for the population.

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