Abstract:
:The aim of this paper is to briefly outline a Bayesian approach to cost-effectiveness analysis (CEA). Historically, frequentists have been cautious of Bayesian methodology, which is often held as synonymous with a subjective approach to statistical analysis. In this paper, the potential overlap between Bayesian and frequentist approaches to CEA is explored--the focus being on the empirical and uninformative prior-based approaches to Bayesian methods rather than the use of subjective beliefs. This approach emphasizes the advantage of a Bayesian interpretation for decision-making while retaining the robustness of the frequentist approach. In particular the use of cost-effectiveness acceptability curves is examined. A traditional frequentist approach is equivalent to a Bayesian approach assuming no prior information, while where there is pre-existing information available from which to construct a prior distribution, an empirical Bayes approach is equivalent to a frequentist approach based on pooling the available data. Cost-effectiveness acceptability curves directly address the decision-making problem in CEA. Although it is argued that their interpretation as the probability that an intervention is cost-effective given the data requires a Bayesian interpretation, this should generate no misgivings for the frequentist.
journal_name
Health Econjournal_title
Health economicsauthors
Briggs AHdoi
10.1002/(sici)1099-1050(199905)8:3<257::aid-hec427keywords:
subject
Has Abstractpub_date
1999-05-01 00:00:00pages
257-61issue
3eissn
1057-9230issn
1099-1050pii
10.1002/(SICI)1099-1050(199905)8:3<257::AID-HEC427journal_volume
8pub_type
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