Optimality of Equal vs. Unequal Cluster Sizes in Multilevel Intervention Studies: A Monte Carlo Study for Small Sample Sizes |
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Authors: | Math J J M Candel Gerard J P Van Breukelen Larissa Kotova Martijn P F Berger |
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Institution: | 1. Department of Methodology and Statistics , Maastricht University , Maastricht, The Netherlands Math.Candel@stat.unimaas.nl;3. Department of Methodology and Statistics , Maastricht University , Maastricht, The Netherlands;4. Rabobank Nederland , Utrecht, The Netherlands |
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Abstract: | 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. |
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Keywords: | D-optimality D s -optimality Mean squared error Multilevel intervention studies Relative efficiency (Restricted) maximum likelihood Unequal cluster sizes |
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