Skip to main content
    • Aa
    • Aa
  • Get access
    Check if you have access via personal or institutional login
  • Cited by 6
  • Cited by
    This article has been cited by the following publications. This list is generated based on data provided by CrossRef.

    Round, Jeff Leurent, Baptiste and Jones, Louise 2014. A cost-utility analysis of a rehabilitation service for people living with and beyond cancer. BMC Health Services Research, Vol. 14, Issue. 1,

    Gregori, D. Petrinco, M. Bo, S. Desideri, A. Merletti, F. and Pagano, E. 2011. Regression models for analyzing costs and their determinants in health care: an introductory review. International Journal for Quality in Health Care, Vol. 23, Issue. 3, p. 331.

    Soares, Marta O. Bojke, Laura Dumville, Jo Iglesias, Cynthia Cullum, Nicky and Claxton, Karl 2011. Methods to elicit experts’ beliefs over uncertain quantities: application to a cost effectiveness transition model of negative pressure wound therapy for severe pressure ulceration. Statistics in Medicine, Vol. 30, Issue. 19, p. 2363.

    Gibert, Karina García-Alonso, Carlos and Salvador-Carulla, Luis 2010. Integrating clinicians, knowledge and data: expert-based cooperative analysis in healthcare decision support. Health Research Policy and Systems, Vol. 8, Issue. 1,

    Hoch, Jeffrey S Rockx, Marie Antoinette and Krahn, Andrew D 2006. Using the net benefit regression framework to construct cost-effectiveness acceptability curves: an example using data from a trial of external loop recorders versus Holter monitoring for ambulatory monitoring of "community acquired" syncope. BMC Health Services Research, Vol. 6, Issue. 1,

    Stevens, John W. O'Hagan, Anthony and Miller, Paul 2003. Case study in the Bayesian analysis of a cost-effectiveness trial in the evaluation of health care technologies: Depression. Pharmaceutical Statistics, Vol. 2, Issue. 1, p. 51.

  • International Journal of Technology Assessment in Health Care, Volume 18, Issue 4
  • December 2002, pp. 782-790


  • John W. Stevens (a1) and Anthony O'Hagan (a2)
  • DOI:
  • Published online: 01 December 2002

The Bayesian approach to statistics has been growing rapidly in popularity as an alternative to the frequentist approach in the appraisal of heathcare technologies in clinical trials. Bayesian methods have significant advantages over classical frequentist statistical methods and the presentation of evidence to decision makers. A fundamental feature of a Bayesian analysis is the use of prior information as well as the clinical trial data in the final analysis. However, the incorporation of prior information remains a controversial subject that provides a potential barrier to the acceptance of practical uses of Bayesian methods. The pur pose of this paper is to stimulate a debate on the use of prior information in evidence submitted to decision makers. We discuss the advantages of incorporating genuine prior information in cost-effectivene ss analyses of clinical trial data and explore mechanisms to safeguard scientific rigor in the use of such prior information.

Recommend this journal

Email your librarian or administrator to recommend adding this journal to your organisation's collection.

International Journal of Technology Assessment in Health Care
  • ISSN: 0266-4623
  • EISSN: 1471-6348
  • URL: /core/journals/international-journal-of-technology-assessment-in-health-care
Please enter your name
Please enter a valid email address
Who would you like to send this to? *