I have a dataset that has 17 variables. 9 categorical and 8 continuous. Some have more than 2 levels. I've reduced the dimensionality significantly. I am looking for strategies to test for colinearity within the dataset before I construct the logistic model and test for collinearity there.
I can just split the model into subsets of the categorical and continuous data then test fo collinearity there. Then do so again for the logistic model with an Anova test. But I am not sure what the best options might be.