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Optimal predictive sample size for case–control studies

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  • Fulvio De Santis
  • Marco Perone Pacifico
  • Valeria Sambucini

Abstract

Summary. The identification of factors that increase the chances of a certain disease is one of the classical and central issues in epidemiology. In this context, a typical measure of the association between a disease and risk factor is the odds ratio. We deal with design problems that arise for Bayesian inference on the odds ratio in the analysis of case–control studies. We consider sample size determination and allocation criteria for both interval estimation and hypothesis testing. These criteria are then employed to determine the sample size and proportions of units to be assigned to cases and controls for planning a study on the association between the incidence of a non‐Hodgkin's lymphoma and exposition to pesticides by eliciting prior information from a previous study.

Suggested Citation

  • Fulvio De Santis & Marco Perone Pacifico & Valeria Sambucini, 2004. "Optimal predictive sample size for case–control studies," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 53(3), pages 427-441, August.
    • Handle: RePEc:bla:jorssc:v:53:y:2004:i:3:p:427-441
    DOI: 10.1111/j.1467-9876.2004.0d490.x
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    Cited by:

    1. Jörg Martin & Clemens Elster, 2021. "The variation of the posterior variance and Bayesian sample size determination," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(4), pages 1135-1155, October.
    2. Stamey, James & Gerlach, Richard, 2007. "Bayesian sample size determination for case-control studies with misclassification," Computational Statistics & Data Analysis, Elsevier, vol. 51(6), pages 2982-2992, March.
    3. Fulvio De Santis & Stefania Gubbiotti, 2021. "Sample Size Requirements for Calibrated Approximate Credible Intervals for Proportions in Clinical Trials," IJERPH, MDPI, vol. 18(2), pages 1-11, January.
    4. Bhramar Mukherjee & Jaeil Ahn & Stephen B. Gruber & Malay Ghosh & Nilanjan Chatterjee, 2010. "Case–Control Studies of Gene–Environment Interaction: Bayesian Design and Analysis," Biometrics, The International Biometric Society, vol. 66(3), pages 934-948, September.

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