I am working on a clinical trial testing an innovative rehabilitation therapy on patients and I would like some suggestions on how to analyse the data.
The study design is: 2-groups: conventional (n=17) vs innovative (n=15) treatment; 4-time points (pre-therapy, T0; halfway through the therapy period, T1; end of therapy, T2; 2 months follow-up, T3). As output, we record a continuous variable: time (in seconds) to walk from point A to point B. We record multiple values for each subject at each time point (T0,T1,T2,T3).
I have seen articles where the authors used ANOVA to evaluate the change in performance within each group. However, I would also like to evaluate the difference between groups, preferably at each time point as well. I have noticed other studies using Linear Mixed Models.
I thought of setting as Fixed effect: Group, Time-point; Random effect: intercept per subject, Group per subject.
However, I am not an expert of this technique and I do not really know how to apply it, or how to write it in R/Statsmodels. Can you please help me understand how to set it up and how to write it on a coding platform?
Thanks a lot in advance!