![]() ![]() "The true reason of the apparent inconsitency is that the effect size in ANCOVA procedure is defined as f = s_effect / s_error (as stated in the corresponding effect size dialog). However, Edgar Erdfelder, one of the founding fathers of G*Power explained us in a private correspondence: ![]() using f=0.125) gives you the expected N of 128. As a result, the effect size is doubled: in your example this results in f = 2x0.25 = 0.5." We think this is a flaw, since this assumption is counterintuitive and not clearly documented. a positive effect in group A versus a similar negative effect in group B - see the image below). "When calculating the sample size for "ANOVA: Repeated measures, within-between interaction" G*Power assumes a so-called "double dissociation effect" (i.e. We thought the following was an explanation for the matter: This is a topic for seriously misunderstanding G*Power! Thank you for bringing this up. What am I missing here? Why is there such a big difference between the required sample sizes? What additional assumptions does the RM-ANOVA approach require to justify this big of a difference? Sphericity shouldn't be an issue since I have only 2 measurement points. In this case, the main effects of time and condition are not of interest the interaction of condition X time is what matters.īut when I calculate the required sample size for this approach in GPower, it reports an estimated sample size of N= 34 (17 per group!) for the whole sample. However, a repeated measures ANOVA approach can also be justified to analyse pretest-posttest-data with two groups ( ). For the given parameters, GPower reports an N of 128 (64 per group). Typically, ANCOVAs are used to analyse clinical trials (comparing posttest values while correcting for baseline values). ![]() I am assuming a medium sized effect (f= 0.25), alpha of. Control) and am currently trying to work out the required sample size. Post-intervention) and two groups (Treatment vs. I want to conduct a randomized pre-post intervention study with two measurement points (1. ![]()
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