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I am having trouble deciding what type of analysis to use for the following data:

I have two groups (one control, one treatment) and took a pre-measure of my dependent variable, and then 3 post-measures.

I am interested in understanding if the treatment affected the dependent variable over the course of the study.

I originally did a rmANOVA, and found no significant interaction (treatmentxtime), but found a main effect of the treatment. I think this means that the treatment group was different than the control over the entire study, including before treatment began.

My question is, is there a better analysis that takes into account if the groups were in fact different before treatment? With a t-test, they were not different, but somehow with all of the data throughout the experiment, they are different.

Thanks!

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One simple way would be to compute gain scores - post1 - pre, post2 - pre, and post3 - pre and do your analysis in terms of treatment and period (1st, 2nd, or 3rd post meas) -- or average the 3 gain scores so that you just have 1 value for each subject.

A lot depends on what exactly those pot-treatment measures are. There must be a reason for 3 of them rather than just 1. Can you say more about that, and I may add to my answer.

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