Bayesian estimation of cost-effectiveness from censored data

Daniel F. Heitjan, Clara Yuri Kim, Huiling Li

Research output: Contribution to journalArticlepeer-review

22 Scopus citations


We describe a Bayesian methodology for estimating the cost-effectiveness of a new treatment compared to a standard in a clinical trial, when censoring of survival, the effectiveness variable, induces censoring of total cost. The statistical model assumes that survival follows a Weibull distribution and that total health care cost follows a gamma distribution whose mean has a linear regression on survival time. We summarize the posterior distributions of key parameters by importance sampling. We illustrate the method with an analysis of data from a randomized clinical trial of a treatment for cardiovascular disease.

Original languageEnglish (US)
Pages (from-to)1297-1309
Number of pages13
JournalStatistics in Medicine
Issue number8
StatePublished - Apr 30 2004


  • Bayesian inference
  • Clinical trials
  • Cost-effectiveness ratios
  • Importance sampling
  • Net monetary benefit

ASJC Scopus subject areas

  • Epidemiology
  • Statistics and Probability


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