Optimality of equal vs. unequal cluster sizes in multilevel intervention studies: A Monte Carlo study for small sample sizes

M.J.J.M. Candel*, G.J.P. van Breukelen, L. Kotova, M.P.F. Berger

*Corresponding author for this work

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Optimality of equal versus unequal cluster sizes in the context of multilevel intervention studies is examined. A Monte Carlo study is done to examine to what degree asymptotic results on the optimality hold for realistic sample sizes and for different estimation methods. The relative D-criterion, comparing equal versus unequal cluster sizes, almost always exceeded 85%, implying that loss of information due to unequal cluster sizes can be compensated for by increasing the number of clusters by 18%. The simulation results are in line with asymptotic results, showing that, for realistic sample sizes and various estimation methods, the asymptotic results can be used in planning multilevel intervention studies.
Original languageEnglish
Pages (from-to)222-239
JournalCommunications in Statistics-Simulation and Computation
Issue number1
Publication statusPublished - 1 Jan 2008

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