Journal
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
Volume 37, Issue 1, Pages 222-239Publisher
TAYLOR & FRANCIS INC
DOI: 10.1080/03610910701724052
Keywords
D-optimality; D-s-optimality; mean squared error; multilevel intervention studies; relative efficiency; (restricted) maximum likelihood; unequal cluster sizes
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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.
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