Hi, If possible, I'd like to obtain advice regarding the correct / best statistical test to use for a certain study design. A summary of the brief study design is as follows:

"This study used a randomised controlled cross-over pre-post study design in which eighteen (n=18) strength-trained participants undertook a 12-week (3 interventions x 4 weeks) whole-body strength training programme (refer to attached .png files as visual of study design). Participants were randomly distributed to groups that performed all 3 treatments conditions in order to complete the study. Participants remained in the same post-exercise intervention strategy i.e. cold (CWI) or hot water immersion (HWI), or a control (CON) condition for the duration of each 4-week block, and cross-over thereafter between interventions in order to complete the study."

Previously, I have been advised to apply Linear Mixed Modelling, or Factorial / Repeated Measures ANOVA for this study design. As there is some missing data, I understand that LMM handles missing data better than ANOVA, and as such I will proceed using LMM.

As I used a pre-post study design, the post-test of 1 block, was simultaneously the pre-test for the next block, and so forth. In terms of my data layout and analysis, should I treat time as a repeated measure using absolute raw values, or should I calculate the difference (post-pre) and assign that raw difference to a particular treatment intervention?

In addition to independent variables (treatment), I would like to incorporate 2 covariates into the model to help explain the outcomes.

Sample code that I will use is as follows:

Code:
 xtmixed yvar xvar c.covar1##i.covar2 || _all: R.id || trt: , reml nolog
where yvar is dependent variable; xvar is independent variable; covar 1 is continuous covariate; covar2 is categorical covariate;

As this was a random cross-over study design, how or should I factor in the order the participants moved through the intervention? Is this what I need to understand as being either crossed or nested?

Appreciate any advice you can provide.
Thanks, Barry