Estimating the Bayesian loss function. A conjoint analysis approach.

M V Bala; J Mauskopf

doi:10.1017/s0266462301104046

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Estimating the Bayesian loss function. A conjoint analysis approach.

M V Bala·J Mauskopf

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Abstract

Current health economic literature does not provide clear guidelines on how uncertainty around cost-effectiveness estimates should be incorporated into economic decision models. Bayesian analysis is a promising alternative to classical statistics for incorporating uncertainty in economic analysis. Estimating a loss function that relates outcomes to societal welfare is a key component of Bayesian decision analysis. Health economists commonly compute the loss function based on the quality-adjusted life-years associated with each outcome. However, if welfare economics is adopted as the theoretical foundation of the analysis, a loss function based in cost-benefit analysis (CBA) may be more appropriate. CBA has not found wide use in health economics due to practical issues associated with estimating such a loss function. In this paper, we present a method based in conjoint analysis for estimating the CBA loss function that can be applied in practice. We illustrate the use of the methodology using data from a pilot study.

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Acute Disease Bayes Theorem Clinical Trials as Topic Consumer Behavior Decision Making Health Care Rationing Humans Models, Econometric Myocardial Infarction Pilot Projects Quality-Adjusted Life Years Journal Article Validation Study

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M V Bala, J Mauskopf. 2001. Estimating the Bayesian loss function. A conjoint analysis approach.. https://doi.org/10.1017/s0266462301104046

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