I could need some help on how to choose the correct way to analyze the data I have collected.
I conducted an experiment with two groups (control condition vs. experimental condition). The continuous dependent variable was tested twice after the intervention for each subject. That is, I have one between subjects-factor (condition) and one within subjects-factor (test time). Additionally, I have one continuous control variable that ideally I would like to include in my model, but this is not a priority.
Basically, I would like to test the following hypothesis:
- Is there a difference between the two conditions at test time 1?
- Is the change between test time 1 and test time 2 different for the two conditions (interaction condition/test time)?
These are the ideas I have come up with:
A hierarchical linear model/multilevel model
...with time as a within subjects factor, condition as a between subjects factor and an interaction of both to analyze the change between test times 1 and 2.
Advantage: I can include my control variable and all hypothesis can be tested in one model.
Disadvantage: Is it correct? Plus, my supervisor/reviewer would prefer a more simple approach.
A repeated measures ANOVA
... again with time as a within subjects factor, condition as a between subjects factor and an interaction of both to analyze the change between test times 1 and 2.
Advantage: Similar to multilevel approach, I could include my control variable.
Disadvantage: I'm not sure if it is correct. Additionally, it may still be too complicated. And I would need to perform post-hoc analyses.
Two t-tests
One t-test for the difference between the two conditions at test time 1. Then I would calculate the difference between test time 1 and test time 2 and in a second t-test would test if this difference differs between the two conditions.
Advantage: "Simple". If I put the variables in an ANCOVA I could additionally control for my continuous variable.
Disadvantage: Wrong? Okay? I'm not sure about it.
Summary
I have to meet two demands: I want to analyze the data correctly and I have to do it as simple as possible. Thus, if it would be okay/correct to analyze the data with the two t-tests approach I would probably go for it, as my supervisor/reviewer would be happy with it. However, if it is not correct, I would be okay with one of the "more complicated" approaches, if I were at least sure that they are okay.
