I'm using lmer to analyse my data, building nested models and using anova() to compare them against each other in an incremental way. Now, I know enough to only test a single term at a time (i.e. only one term changes between model 1 and model 2, so that when I compare them with anova I know what question I am answering), my question rather relates to the order in which you should test your terms of interest.
Is there a preference or a rule that states whether you should fit your fixed effect terms before your random effect terms? If so, what is the reason?
Thanks all very much