This is my first post and as I’m a recent M Biostats graduate, there are fairly large gaps in my knowledge, so please go easy on me. I figure this will be a good place to learn…
I have a question about how to handle power/sample size calculations in clinical trials. My understanding (based on what has been taught in the course) of sample size calculations in an RCT context has been about two-group comparisons (treatment vs control) for means, proportion, etc.
But in many RCT’s one is interested in the variation in treatment effect over time - i.e. the group by time interaction. In the longitudinal study then, such sample size calculations as described above really only estimate sample size/power for the hypothesised main effect at the end of the study.
Does this effectively mean that whenever one anticipates testing a group x time interaction in the subsequent modelling, their power calculations should be based on an interaction term (which I understand will result in a larger sample size?) rather than just a main effect?
Apologies if the answer is obvious but as I said, there’s still a lot I have to learn.