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Assessing and comparing costs: how robust are the bootstrap and methods based on asymptotic normality?

Author

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  • Anthony O'Hagan

    (Department of Probability and Statistics, University of Sheffield, UK)

  • John W. Stevens

    (AstraZeneca R&D Charnwood, UK)

Abstract

This article addresses and challenges some common perceptions in the statistical assessment of costs and cost-effectiveness in health economics. Cost data typically exhibit highly skew distributions. Two techniques whose validity does not depend on any specific form of underlying distribution are the bootstrap and methods based on asymptotic normality of sample means. These methods are generally thought to be appropriate for the analysis of cost data. We argue that, even when these methods are technically valid, they may often lead to inefficient and even misleading inferences. It is important to apply methods that recognise the skewness in cost data. We further demonstrate that it may also be important to incorporate relevant prior information in a Bayesian analysis. Copyright © 2002 John Wiley & Sons, Ltd.

Suggested Citation

  • Anthony O'Hagan & John W. Stevens, 2003. "Assessing and comparing costs: how robust are the bootstrap and methods based on asymptotic normality?," Health Economics, John Wiley & Sons, Ltd., vol. 12(1), pages 33-49.
  • Handle: RePEc:wly:hlthec:v:12:y:2003:i:1:p:33-49 DOI: 10.1002/hec.699
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    References listed on IDEAS

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    1. Andrew H. Briggs & David E. Wonderling & Christopher Z. Mooney, 1997. "Pulling cost-effectiveness analysis up by its bootstraps: A non-parametric approach to confidence interval estimation," Health Economics, John Wiley & Sons, Ltd., vol. 6(4), pages 327-340.
    2. Maiwenn J. Al & Ben A. Van Hout, 2000. "A Bayesian approach to economic analyses of clinical trials: the case of stenting versus balloon angioplasty," Health Economics, John Wiley & Sons, Ltd., vol. 9(7), pages 599-609.
    3. Andrew H. Briggs, 1999. "A Bayesian approach to stochastic cost-effectiveness analysis," Health Economics, John Wiley & Sons, Ltd., vol. 8(3), pages 257-261.
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    Citations

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    Cited by:

    1. Sundström, David, 2016. "On Specification and Inference in the Econometrics of Public Procurement," Umeå Economic Studies 931, Umeå University, Department of Economics.
    2. Richard M. Nixon & David Wonderling & Richard D. Grieve, 2010. "Non-parametric methods for cost-effectiveness analysis: the central limit theorem and the bootstrap compared," Health Economics, John Wiley & Sons, Ltd., vol. 19(3), pages 316-333.
    3. 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.
    4. Thompson, Simon G. & Nixon, Richard M. & Grieve, Richard, 2006. "Addressing the issues that arise in analysing multicentre cost data, with application to a multinational study," Journal of Health Economics, Elsevier, vol. 25(6), pages 1015-1028, November.
    5. 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.
    6. Gianluca Baio & Laura Magazzini & Claudia Oglialoro & Fabio Pammolli & Massimo Riccaboni, 2005. "Medical Devices: Competitiveness and Impact on Public Health Expenditure," Working Papers CERM 05-2005, Competitività, Regole, Mercati (CERM).
    7. Sundström, David, 2014. "It’s All in the Interval - An imperfect measurements approach to estimate bidders’ primitives in auctions," Umeå Economic Studies 899, Umeå University, Department of Economics, revised 17 Jun 2016.
    8. Caterina Conigliani, 2008. "A bayesian model averaging approach with non-informative priors for cost-effectiveness analyses in health economics," Departmental Working Papers of Economics - University 'Roma Tre' 0094, Department of Economics - University Roma Tre.
    9. Bebu, Ionut & Luta, George & Mathew, Thomas & Kennedy, Paul A. & Agan, Brian K., 2016. "Parametric cost-effectiveness inference with skewed data," Computational Statistics & Data Analysis, Elsevier, vol. 94(C), pages 210-220.
    10. Anne Prenzler & Bernd Bokemeyer & J.-Matthias Schulenburg & Thomas Mittendorf, 2011. "Health care costs and their predictors of inflammatory bowel diseases in Germany," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 12(3), pages 273-283, June.
    11. Caterina Conigliani & Andrea Tancredi, 2006. "Comparing parametric and semi-parametric approaches for bayesian cost-effectiveness analyses in health economics," Departmental Working Papers of Economics - University 'Roma Tre' 0064, Department of Economics - University Roma Tre.
    12. Casey Quinn, 2005. "Generalisable regression methods for costeffectiveness using copulas," Health, Econometrics and Data Group (HEDG) Working Papers 05/13, HEDG, c/o Department of Economics, University of York.
    13. O'Hagan, Anthony & Stevens, John W., 2004. "On estimators of medical costs with censored data," Journal of Health Economics, Elsevier, vol. 23(3), pages 615-625, May.
    14. Caterina Conigliani & Andrea Tancredi, 2009. "A Bayesian model averaging approach for cost-effectiveness analyses," Health Economics, John Wiley & Sons, Ltd., vol. 18(7), pages 807-821.

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