Measuring and illustrating statistical evidence in a cost-effectiveness analysis

Jeffrey S Hoch, Jeffrey D. Blume

Research output: Contribution to journalArticle

13 Citations (Scopus)

Abstract

Recently, there has been much interest in using the cost-effectiveness acceptability curve (CEAC) to measure the statistical evidence of cost-effectiveness. The CEAC has two well established but fundamentally different interpretations: one frequentist and one Bayesian. As an alternative, we suggest characterizing the statistical evidence about cost-effectiveness using the likelihood function (the key element of both approaches). Its interpretation is neither dependent on the sample space nor on the prior distribution. Moreover, the probability of observing misleading evidence is low and controllable, so this approach is justifiable in the traditional sense of frequentist long-run behaviour. We propose a new graphic for displaying the evidence about cost-effectiveness and explore the strengths of likelihood methods using data from an economic evaluation of a Program in Assertive Community Treatment (PACT).

Original languageEnglish (US)
Pages (from-to)476-495
Number of pages20
JournalJournal of Health Economics
Volume27
Issue number2
DOIs
StatePublished - Mar 2008
Externally publishedYes

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Cost-Benefit Analysis
Community Mental Health Services
Likelihood Functions

Keywords

  • Cost-effectiveness analysis
  • Likelihood methods
  • Net benefit regression framework

ASJC Scopus subject areas

  • Health Policy
  • Public Health, Environmental and Occupational Health

Cite this

Measuring and illustrating statistical evidence in a cost-effectiveness analysis. / Hoch, Jeffrey S; Blume, Jeffrey D.

In: Journal of Health Economics, Vol. 27, No. 2, 03.2008, p. 476-495.

Research output: Contribution to journalArticle

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