title: Collinearity after accounting for random/mixed effects
body: <p>could two/more predictors become more/less collinear after accounting for random effects? </p>
  
  <p>In my case I have tested for collinearity prior to modelling, e.g. using VIF, and everything checks out. However, the ranking (using IC) of different models makes me uncertain whether it truly can separate between the predictors.</p>
  
  <p>Any ideas?</p>
  
  <p>ps! Can someone with higher rep than I add a more relevant tag such as collinearity?</p>