This is pretty general, but what are the pros and cons of including additional levels in multilevel model (linear mixed model)?
I have a data containing information on multilevel administrative division of the country and most of the levels are more or less of interest for me. Sample size is not a problem in here. On one hand, simpler models are in most cases better, on another, including additional levels would enable me to compare the variances on different levels. I found examples of 4-level models in the literature, but I haven't seen any practical advise on that. Could you provide any arguments and/or literature on that?