I have a very basic question. I have ordinal
predictors in my LR analyses. They have been treated
as continuous. Some of them are highly correlated and
test positive for collinearity (VIFs, Condition Index,
etc). As there are 4-5 different values for each
predictor. Is this confounding or collinearity or
both? I have been dropping one from my multivariate
as you are encouraged to do with collinearity. But,
with confounding, you are encouraged to retain them.
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