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Balancing the Number and Size of Sites: An Economic Approach to the Optimal Design of Cluster Samples

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  • Connelly, Luke B.

Abstract

The design of randomised controlled trials (RCTs) entails decisions that have economic, as well as statistical implications. In particular, the choice of an individual or cluster randomisation design may affect the cost of achieving the desired level of power, other things equal. Furthermore, if cluster randomisation is chosen, the researcher must decide how to balance the number of clusters, or "sites", and the size of each site. This paper investigates these interrelated statistical and economic issues. Its principal purpose is to elucidate the statistical and economic trade-offs to assist researchers to employ RCT designs that have desired economic, as well as statistical, properties.

Suggested Citation

  • Connelly, Luke B., 2003. "Balancing the Number and Size of Sites: An Economic Approach to the Optimal Design of Cluster Samples," MPRA Paper 14676, University Library of Munich, Germany.
    • Handle: RePEc:pra:mprapa:14676
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    File URL: https://mpra.ub.uni-muenchen.de/14676/1/MPRA_paper_14676.pdf
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    References listed on IDEAS

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    6. Conlisk, John, 1973. "Choice of Response Functional Form in Designing Subsidy Experiments," Econometrica, Econometric Society, vol. 41(4), pages 643-656, July.
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    8. Stephen Howes & Jean Olson Lanjouw, 1998. "Does Sample Design Matter For Poverty Rate Comparisons?," Review of Income and Wealth, International Association for Research in Income and Wealth, vol. 44(1), pages 99-109, March.
    9. Fiebig, Denzil G. & Bartels, Robert & Aigner, Dennis J., 1991. "A random coefficient approach to the estimation of residential end-use load profiles," Journal of Econometrics, Elsevier, vol. 50(3), pages 297-327, December.
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    Citations

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    Cited by:

    1. Chris Schilling & Michelle Tew & Samantha Bunzli & Cade Shadbolt & L. Stefan Lohmander & Zsolt J. Balogh & Francesco Paolucci & Peter F. Choong & Michelle M. Dowsey & Philip Clarke, 2023. "An Economic Model for Estimating Trial Costs with an Application to Placebo Surgery Trials," Applied Health Economics and Health Policy, Springer, vol. 21(2), pages 263-273, March.
    2. Khanam, Rasheda & Nghiem, Hong Son & Connelly, Luke B., 2009. "Child health and the income gradient: Evidence from Australia," Journal of Health Economics, Elsevier, vol. 28(4), pages 805-817, July.
    3. Zuchao Shen & Benjamin Kelcey, 2020. "Optimal Sample Allocation Under Unequal Costs in Cluster-Randomized Trials," Journal of Educational and Behavioral Statistics, , vol. 45(4), pages 446-474, August.
    4. Takashi Kikuchi & John Gittins, 2010. "A behavioural Bayes approach for sample size determination in cluster randomized clinical trials," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 59(5), pages 875-888, November.
    5. Mark R. Powell, 2014. "Optimal Food Safety Sampling Under a Budget Constraint," Risk Analysis, John Wiley & Sons, vol. 34(1), pages 93-100, January.

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    More about this item

    Keywords

    Cluster sample; optimal design; economic analysis;
    All these keywords.

    JEL classification:

    • C42 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Survey Methods
    • C93 - Mathematical and Quantitative Methods - - Design of Experiments - - - Field Experiments
    • D24 - Microeconomics - - Production and Organizations - - - Production; Cost; Capital; Capital, Total Factor, and Multifactor Productivity; Capacity

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