IDEAS home Printed from https://ideas.repec.org/a/sae/medema/v21y2001i3p219-230.html
   My bibliography  Save this article

Bayesian Assessment of Sample Size for Clinical Trials of Cost-Effectiveness

Author

Listed:
  • Anthony O’Hagan

    (University of Sheffield, United Kingdom)

  • John W. Stevens

    (AstraZeneca R&!D Charnwood, United Kingdom)

Abstract

The authors present an analysis of the choice of sample sizes for demonstrating cost-effectiveness of a new treatment or procedure, when data on both cost and efficacy will be collected in a clinical trial. The Bayesian approach to statistics is employed, as well as a novel Bayesian criterion that provides insight into the sample size problem and offers a very flexible formulation.

Suggested Citation

  • Anthony O’Hagan & John W. Stevens, 2001. "Bayesian Assessment of Sample Size for Clinical Trials of Cost-Effectiveness," Medical Decision Making, , vol. 21(3), pages 219-230, May.
    • Handle: RePEc:sae:medema:v:21:y:2001:i:3:p:219-230
    DOI: 10.1177/0272989X0102100307
    as

    Download full text from publisher

    File URL: https://journals.sagepub.com/doi/10.1177/0272989X0102100307
    Download Restriction: no
    File URL: https://libkey.io/10.1177/0272989X0102100307?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Briggs, Andrew & Tambour, Magnus, 1998. "The design and analysis of stochastic cost-effectiveness studies for the evaluation of health care interventions," SSE/EFI Working Paper Series in Economics and Finance 234, Stockholm School of Economics.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Thompson, Nathanael M. & Brorsen, B. Wade & DeVuyst, Eric A. & Lusk, Jayson L., 2016. "Random Sampling of Beef Cattle for Genetic Testing: Optimal Sample Size Determination," 2016 Annual Meeting, February 6-9, 2016, San Antonio, Texas 229195, Southern Agricultural Economics Association.
    2. Andrew Willan, 2011. "Sample Size Determination for Cost-Effectiveness Trials," PharmacoEconomics, Springer, vol. 29(11), pages 933-949, November.
    3. Alan Brennan & Samer A. Kharroubi, 2007. "Expected value of sample information for Weibull survival data," Health Economics, John Wiley & Sons, Ltd., vol. 16(11), pages 1205-1225, November.
    4. Pierpaolo Brutti & Fulvio Santis & Stefania Gubbiotti, 2014. "Bayesian-frequentist sample size determination: a game of two priors," METRON, Springer;Sapienza Università di Roma, vol. 72(2), pages 133-151, August.
    5. Theodoros Mantopoulos & Paul M. Mitchell & Nicky J. Welton & Richard McManus & Lazaros Andronis, 2016. "Choice of statistical model for cost-effectiveness analysis and covariate adjustment: empirical application of prominent models and assessment of their results," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 17(8), pages 927-938, November.
    6. Daniel P Beavers & James D Stamey, 2018. "Bayesian sample size determination for cost-effectiveness studies with censored data," PLOS ONE, Public Library of Science, vol. 13(1), pages 1-16, January.
    7. Henry Glick, 2011. "Sample Size and Power for Cost-Effectiveness Analysis (Part 1)," PharmacoEconomics, Springer, vol. 29(3), pages 189-198, March.
    8. Miguel A. Negrín & Francisco J. Vázquez‐Polo, 2006. "Bayesian cost‐effectiveness analysis with two measures of effectiveness: the cost‐effectiveness acceptability plane," Health Economics, John Wiley & Sons, Ltd., vol. 15(4), pages 363-372, April.
    9. C. Armero & G. García‐Donato & A. López‐Quílez, 2010. "Bayesian methods in cost–effectiveness studies: objectivity, computation and other relevant aspects," Health Economics, John Wiley & Sons, Ltd., vol. 19(6), pages 629-643, June.
    10. F. J. Vázquez‐Polo & M. A. Negrín Hernández & B. González López‐Valcárcel, 2005. "Using covariates to reduce uncertainty in the economic evaluation of clinical trial data," Health Economics, John Wiley & Sons, Ltd., vol. 14(6), pages 545-557, June.
    11. Alan Brennan & Samer A. Kharroubi, 2007. "Expected value of sample information for Weibull survival data," Health Economics, John Wiley & Sons, Ltd., vol. 16(11), pages 1205-1225.
    12. A. Gafni & S. D. Walter & S. Birch & P. Sendi, 2008. "An opportunity cost approach to sample size calculation in cost‐effectiveness analysis," Health Economics, John Wiley & Sons, Ltd., vol. 17(1), pages 99-107, January.
    13. P. Brutti & F. Santis & S. Gubbiotti, 2013. "Robust Bayesian monitoring of sequential trials," METRON, Springer;Sapienza Università di Roma, vol. 71(1), pages 81-95, June.
    14. Andrew R. Willan & Matthew E. Kowgier, 2008. "Cost‐effectiveness analysis of a multinational RCT with a binary measure of effectiveness and an interacting covariate," Health Economics, John Wiley & Sons, Ltd., vol. 17(7), pages 777-791, July.
    15. Simon Eckermann & Andrew R. Willan, 2009. "Globally optimal trial design for local decision making," Health Economics, John Wiley & Sons, Ltd., vol. 18(2), pages 203-216, February.
    16. Fulvio De Santis & Stefania Gubbiotti, 2021. "On the predictive performance of a non-optimal action in hypothesis testing," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 30(2), pages 689-709, June.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Henry Glick, 2011. "Sample Size and Power for Cost-Effectiveness Analysis (Part 1)," PharmacoEconomics, Springer, vol. 29(3), pages 189-198, March.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:sae:medema:v:21:y:2001:i:3:p:219-230. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: SAGE Publications (email available below). General contact details of provider: .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.