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Choosing Sample Sizes to Maximize Expected Health Benefits Subject to a Constraint on Total Trial Costs

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  • Stuart G. Baker
  • Kurt Heidenberger

Abstract

The authors present a method for choosing sample sizes for randomized controlled trials that maximizes expected health benefits (measured in expected discounted life years gained) subject to the decision maker's budget constraint. In comparison with similar approaches, the method introduces richer and more realistic models for the following quantities: costs and benefits during and after the trial, rates of adopting interventions after a positive rec ommendation, the distribution of data collected in the trial, and the decision to make a positive recommendation based on the results of the trial. Although the methodology is applicable to any type of trial, the emphasis in the paper is on prevention trials. Calculations involve Monte Carlo methods. An example is provided.

Suggested Citation

  • Stuart G. Baker & Kurt Heidenberger, 1989. "Choosing Sample Sizes to Maximize Expected Health Benefits Subject to a Constraint on Total Trial Costs," Medical Decision Making, , vol. 9(1), pages 14-25, February.
    • Handle: RePEc:sae:medema:v:9:y:1989:i:1:p:14-25
    DOI: 10.1177/0272989X8900900104
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    References listed on IDEAS

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    1. Frederick Mosteller & Milton Weinstein, 1985. "Toward Evaluating the Cost-Effectiveness of Medical and Social Experiments," NBER Chapters, in: Social Experimentation, pages 221-250, National Bureau of Economic Research, Inc.
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    Cited by:

    1. Stuart G. Baker, 2024. "Evaluating Risk Prediction with Data Collection Costs: Novel Estimation of Test Tradeoff Curves," Medical Decision Making, , vol. 44(1), pages 53-63, January.
    2. Marion S. Rauner & Walter J. Gutjahr & Kurt Heidenberger & Joachim Wagner & Joseph Pasia, 2010. "Dynamic Policy Modeling for Chronic Diseases: Metaheuristic-Based Identification of Pareto-Optimal Screening Strategies," Operations Research, INFORMS, vol. 58(5), pages 1269-1286, October.

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