0

This is my first project creating my own models. I have 12 possible variables for a habitat model. I am using glms (binominal, logit). I want to check for multicollinearity using the VIF. I have variables on which I will use a log transformation, some that will need quadratic terms and some that will be used with an interaction term with the sex of the animal. I will select the best combination and transformation of variables for a summer season and a winter season model separate by making candidate models for my hypotheses.

Now I wonder what's the smartest/standard way to use the VIF in the process:

Is it a preliminary analysis where I just put all my variables in and kick out the ones with a value over my thresholds (VIF:3, Tolerance:0,2) until all values are below these thresholds?

OR

Do I do it for the complete sets of variables for my 3 hypothesis groups and kick out the ones with a value over my thresholds until all values are below the thresholds?

OR

Do I do it after I found the best candidate models?

Furthermore I am not sure how to include transformations, interaction terms and quadratic terms ? My variables are standardized. Should I include these alterations of the variables or do I use the pure variables (If I do it as a preliminary analysis I probably don't know for sure which variable alterations I will be using in the end)?

Thanks for any help.

Nicole
  • 1
  • 1
  • Please explain what your goal is. For *prediction*, collinearity is no problem. For *inference*, e.g. finding variables with statistically significant influence, collinearity can be a problem, because from a group of collinear variables, each one cna be ommitted without detoriating the prediction. This effect can lead to low significance of these predictors, although they are actually good for predicting the outcome. Note that this question is more appropriate for CrossValidated, because it is about statistical modeling and not about programming. – cdalitz Feb 16 '22 at 16:24
  • Please edit the question to limit it to a specific problem with enough detail to identify an adequate answer. – Community Feb 20 '22 at 05:38

0 Answers0