Robert Birkelbach:

I am writing my Bachelor Thesis in which I want to assess the reading competencies of German elementary school children using the PIRLS2006 data. My levels are classrooms and the individuals. However, my dependent variable is a multiple imputed (m=5) reading test. The problem I have is, that I do not know, whether I can just calculate 5 linear multilevel models and then average all the results (the coefficients, standard deviation, bic, intra class correlation, R2, t-statistics, p-values etc) or if I need different formulas for integrating the results of the five models into one because it is a multilevel analysis? Do you think there’s a better way in solving my problem? I would greatly appreciate if you could help me with a problem regarding my analysis — I am quite a newbie to multilevel modeling and especially to multiple imputation. Also: Is it okay to use frequentist models when the multiple imputation was done bayesian? Would the different philosophies of scientific testing contradict each other?

My reply:

I receommend doing 5 separate analyses, pushing them all the way thru to the end, then combining them using the combining-imputation rules given in the imputatoin chapter of our book. Everything should go fine.