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Effects of Cluster Sizes on Variance Components in Two-Stage Sampling

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  • Valliant Richard

    (Universities of Michigan and Maryland – Joint Program for Survey Methodology, 1218 Lefrak Hall, College Park MD 20742 20742, U.S.A.)

  • Dever Jill A.

    (RTI International, Washington, District of Columbia, U.S.A.)

  • Kreuter Frauke

    (University of Maryland – Joint Program for Survey Methodology, 1218 Lefrak Hall, College Park MD 20742 20742, U.S.A.)

Abstract

Determining sample sizes in multistage samples requires variance components for each stage of selection. The relative sizes of the variance components in a cluster sample are dramatically affected by how much the clusters vary in size, by the type of sample design, and by the form of estimator used. Measures of the homogeneity of survey variables within clusters are related to the variance components and affect the numbers of sample units that should be selected at each stage to achieve the desired precision levels. Measures of homogeneity can be estimated using standard software for random-effects models but the model-based intracluster correlations may need to be transformed to be appropriate for use with the sample design. We illustrate these points and implications for sample size calculation for two-stage sample designs using a realistic population derived from household surveys and the decennial census in the U.S.

Suggested Citation

  • Valliant Richard & Dever Jill A. & Kreuter Frauke, 2015. "Effects of Cluster Sizes on Variance Components in Two-Stage Sampling," Journal of Official Statistics, Sciendo, vol. 31(4), pages 763-782, December.
    • Handle: RePEc:vrs:offsta:v:31:y:2015:i:4:p:763-782:n:12
    DOI: 10.1515/jos-2015-0044
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