Brms - Variable/Feature Selection with ordinal response

[Francesco_De_Vincentis]

Hi everyone,
I’m a new student that want to approach a bayesian statistics. In my study case I have 56 obs and 46 variables (hhcframe dataset) and after estimate the model with shinkrage approach (set prior lasso and horseshoe) and I can’t continue. I applied “Wald Test” (Estimate/Est.Error) but no variable is higher than |1.96|, then what you suggest to me for variable selection and compare these shinkrage models with frequentis approach?

Thank you so much for attention.

[fweber144]

What about these discussions?:

Brms for ordinal outcome (Ridge, LASSO, Elastic Net)

I am De Vincentis Francesco, a Statistics student form University Federico II in Naples (Italy). In this time I work on my thesis in “Variable Selection” and I’d like to apply Bayesian approach to modeling a “hccframe” dataset with 56 observations, 45 regressor, Y ordinal response (Normal, Cirrhosis, Tumor). My first approach is frequentist mode with shrinkage estimator ( Ridge, Lasso and Elastic Net). What do You suggest me with bayesian approach? Could I apply this shrinkage method with “brm…

Variable selection with ordinal model

A year after my previous post, I would like to know if you have experiences on how to perform variable selection with an ordinal regression model, even with sub-optimal strategies like brute force (i.e. checking LOO-IC running a lot of models). I have many predictors so I would spend years in checking all the combinations. Thanks in advance

[Francesco_De_Vincentis]

The second