I'm new to SAS (v9.4) and statistics in general.   I want to do an ordinal logistic regression (N = 430 employees) . My dependent and independent variables are ordinals. Job Satisfaction (scaled from 1 -5) and Work Respect (scaled from 1 - 4).  I have 35 potential covariates (confounders) and I want to come up with a reduced number of variables that are greatly de-correlated from each other before adding them to my model. These covariates are binary, ordinal, continuous, and nominal variables.   I'm at a loss/unsure which SAS function(s) to use to remove / drastically reduce any co-dependencies within these variables. Will de-correlation via GVIF work for all or will CATPCA analysis be enough? The SAS functions I've looked at either work for categorical variables only (ordinals and nominals) or some combination of three out of four variable types.   What do you recommend I do to eliminate collinearity amongst mixed variables?   PS Grok 3 says I need to do individual de-correlation procedures suitable for each variable type. I'm hesitant to believe it for now. I am concerned that, for example, a reduced continuous variable set might correlate with reduced ordinal set, if I perform separate analyses.   EDIT ... made a slight change for better clarity. ... View more