I have control and intervention groups (N = 50 and 75, respectively) for whom 15 tests (all having quantitative results) were done at baseline and at 3 months.
It is not a randomized study and the baseline values in control group ARE different from those of intervention group.
My precise question is: "Does the intervention causes a significant change in values of these tests"
What is the best method for this? Should I perform unpaired t-tests on baseline-follow up differences in 2 groups or should I use anova/regression?
Also, how do I correct for multiple tests being done here?
If this has already been discussed, please point me to the right link(s). Thanks for your help.
Edit: Data is in following format:
ID_NO GRP prepost test1 test2 1 active pre 10 0.074 2 control pre 11 0.053 1 active post 10.8 0.042 2 control post 10.5 0.039 ....
For anova, following can be used (in R):
summary(aov(testresult ~ GRP * prepost + Error(ID_NO/prepost), data=mydata))
Following can be used for regression:
summary(lm(testresult_difference ~ testresult_basal + GRP , data=mydata))
Unpaired t-tests can be used for testing difference (change) in controls vs change in intervention group. Similarly unpaired t-test can be used for comparing post/pre ratio in controls vs that intervention group.
Which method should I use?