Hello, I am currently testing whether I should include certain random effects in my lmer model or not. I use the anova function for that. My procedure so far is to fit the model with a function call to lmer() with REML=TRUE (the default option). Then I call anova() on the two models where one of them does include the random effect to be tested and the other one does not. However, it is well known that the anova() function refits the models with ML (new versions also output a warning that they do so). But in the new version of anova() you can prevent anova() from doing so by setting the option refit=FALSE. In order to test for random effects should I set refit=FALSE in my call to anova() or not? If I do set refit=FALSE the p-values tend to be lower. (Additional question: Are the p-values calculated by anova() anti-conservative when I set refit=FALSE?)
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