Hello,

I have a dataset that contains survey responses from participants attending a training workshop. Surveys were administered prior to training, just after training, and 3 months post training. Moreover, there are a total of 5 trainings were carried out over a period of 2 years; however, there were no major changes in training content or the way the trainings were administered (although the trainers might have changed over time). I am interested in investigating the change in scores from pre to post (to evaluate improvements in score from time 1 to time 2 and retention of improvements from time 2 to time 3). Finally, I'm also interested in determining the effect of certain potential confounders (age, sex, and previous training) on the change in scores.


I am unsure about whether to run a mixed repeated measures ANOVA here with the between subjects variables being year of training (or training batch), age, and sex. Or if it would be more suitable to run a linear two-level mixed effects model with, with time as a fixed-effects predictor and participants as a level 1 cluster. Please advise on what would be more suitable or how to determine the most suitable approach in this case.

Moreover, seeing as the trainings did not change (in terms of content) would it be reasonable to not consider it year or batch of training as a covariate?

Thank you,
Sam