I have continuous response variables that are parameters returned by a reinforcement learning+working memory model. My group variable includes three levels: healthy controls, unipolar depression, and bipolar depression.
I would like to compare the parameters between groups (for example, do people with unipolar depression have a lower reward learning rate than healthy controls), while controlling for age and gender. The parameters are not normally distributed and previous studies used non-parametric tests such as the Kruskal-Wallis H or Mann-Whitney U-test. I would like to control for age and gender, so I researched that the Wilcoxon-Mann-Whitney two-sample rank-sum test is a special case of the proportional odds (PO) ordinal logistic regression model.
Right now, I used the 'orm' function from the 'rms'package in R:
orm(RL_alpha ~ GROUP_any_lifetime_MD + demographics_gender + demographics_age, data = mydata_RLWM)
Does it seem like a valid approach? Are there any alternatives or additional checks?
I am new to the forum and I really appreciate any advice!