In a study, drug was given to tt (treatment) group and not to cc (control) group and blood levels of (say) cholesterol were tested before and after in each subject.
I have following data:
id grp preLevel postLevel diff percentDiff prePostRatio 1 1 tt 140 110 30 0.21 1.27 2 2 tt 150 120 30 0.20 1.25 3 3 cc 135 125 10 0.07 1.08 4 4 cc 155 145 10 0.06 1.07 ...
I can perform t.test or wilcox.test and compare the two groups. But what is the best parameter to analyze: absolute difference, percent difference or pre/post ratio? Or it does not matter and they will all produce same result?
For above data should I use t.test/ wilcox.test or repeated measures anova as described on this page: http://ww2.coastal.edu/kingw/statistics/R-tutorials/repeated.html using following code with rearranged data:
id grp pre_or_post level 1 tt pre 140 1 tt post 110 2 tt pre 150 2 tt post 120 3 cc pre 135 3 cc post 125 ... aov(level ~ grp * pre_or_post + Error(id/pre_or_post), data=mydata)
Also, how will the method of analysis differ if it is a parallel group study with different subjects in treatment and controls groups or it is a cross-over study with same subjects being in treatment and control groups at different times?