1
$\begingroup$

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!

$\endgroup$

1 Answer 1

1
$\begingroup$

The outcome variables don't need to be normally distributed for linear regression to work; what's important is that the residuals around the model predictions be well behaved. See this thread among others on this site.

That said, ordinal regression can be a useful tool for flexible modeling of outcomes. See Frank Harrell's course notes and book for details on types of ordinal regression models (e.g., proportional-odds versus continuation-ratio), the choice of distribution family (proportional odds uses a logistic family, but other choices are possible; see the help page for orm.fit), and ways to check, validate and calibrate models. Chapter 14 of the book has an extended presentation of how to apply ordinal regression, in a case study.

$\endgroup$
1
  • 2
    $\begingroup$ Thank you for the reply! The QQ plot showed strong violations of the normality assumption when I ran the linear regression and previous studies all applied non-parametric tests, so that's why I also want to use non-parametric tests in this situation. I also watched Frank Harrell's course on Youtube, but I will also check out the book! Thanks for sharing that! $\endgroup$ Dec 10, 2021 at 23:02

Your Answer

By clicking “Post Your Answer”, you agree to our terms of service, privacy policy and cookie policy

Not the answer you're looking for? Browse other questions tagged or ask your own question.