I want to conduct a randomized pre-post intervention study with two measurement points (1. Baseline 2. Post-intervention) and two groups (Treatment vs. Control) and am currently trying to work out the required sample size. I am assuming a medium sized effect (f= 0.25), alpha of .05 and a power of .80.
Typically, ANCOVAs are used to analyse clinical trials (comparing posttest values while correcting for baseline values). For the given parameters, GPower reports an N of 128 (64 per group).
However, a repeated measures ANOVA approach can also be justified to analyse pretest-posttest-data with two groups (https://doi.org/10.1177/0962280218789972 ; https://www.theanalysisfactor.com/pre-post-data-repeated-measures/).
In this case, the main effects of time and condition are not of interest; the interaction of condition X time is what matters. But 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. This feels like it can't be trusted. 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.