I have an intervention study with a very small sample size and am trying to decide the best way to analyze it. Any suggestions would be extremely helpful. Here is some more information:

Measurements on 5 different variables were taken at 3 time points: Baseline, Follow-up 1, Follow-up 2

Group 1 (n=14) completed one set of exercises, Group 2 (n=16) completed a different set of exercises, and Group 3 (n=8) completed no exercises.

Ideally, I would like to compare change in all of these groups across all three time points, but my sample size is so small and I know having so many groups, time points, and measurements makes things even more difficult.

Does anyone have suggestions?

Analyses I am considering are:

repeated-measures ANOVA for each variable separately or a repeated-measures MANOVA for all variables, multilevel modeling, separate repeated measures t-tests for each group on each measure (so no statistical between-group comparison), regression with baseline scores as covariates….help!! Thank you so much!