[R-sig-ME] How sinful is it to...

[David Sidhu]

Hi Everyone!

I am conducting a mixed model logistic regression analysis of some simple experimental data in which participants made dichotomous choices. My independent variable has two levels. What I am really interested in is the ability of the independent variable to predict the dependent variable, with the random effects in there simply to allow the best test of this.

I am starting from the point of view that I should “keep it maximal”. That being said my two questions are:

  *   Is there something horrible about keeping in random effects that are highly (or perfectly!) correlated with one another?
     *   If so…would you retain the term that gives you the best model, based on AIC or some other value?
  *   Should you always remove random effects that have 0 variance associated with them?

It seems like the intuitive answer to both of these is yes. But in this paper I am working on, there are several experiments, and for simplicity’s sake it would be much easier to always just have the maximally complex random effects structure that managed to converge, instead of giving details in each case about which terms were removed and why. But is there something horrible wrong with that??

Thanks!

Dave

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David M. Sidhu, MSc
PhD Student
Department of Psychology
University of Calgary


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