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

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  • Anthony O'Hagan
  • John W. Stevens

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, January.
    • 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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    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. Michał Jakubczyk & Bogumił Kamiński, 2010. "Cost‐effectiveness acceptability curves – caveats quantified," Health Economics, John Wiley & Sons, Ltd., vol. 19(8), pages 955-963, August.
    3. 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.
    4. Manuel Gomes & Richard Grieve & Richard Nixon & W. J. Edmunds, 2012. "Statistical Methods for Cost-Effectiveness Analyses That Use Data from Cluster Randomized Trials," Medical Decision Making, , vol. 32(1), pages 209-220, January.
    5. Ilias Goranitis & Joanna Coast & Ed Day & Alex Copello & Nick Freemantle & Emma Frew, 2017. "Maximizing Health or Sufficient Capability in Economic Evaluation? A Methodological Experiment of Treatment for Drug Addiction," Medical Decision Making, , vol. 37(5), pages 498-511, July.
    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. Mohsen Sadatsafavi & Carlo Marra & Stirling Bryan, 2013. "Two‐Level Resampling As A Novel Method For The Calculation Of The Expected Value Of Sample Information In Economic Trials," Health Economics, John Wiley & Sons, Ltd., vol. 22(7), pages 877-882, July.
    8. 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.
    9. 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.
    10. 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, March.
    11. Ben F M Wijnen & Bea Hemmen & Ans I E Bouman & Henk van de Meent & Ton Ambergen & Peter R G Brink & Henk A M Seelen & Silvia M A A Evers, 2019. "Cost-effectiveness of an integrated 'fast track' rehabilitation service for multi-trauma patients: A non-randomized clinical trial in the Netherlands," PLOS ONE, Public Library of Science, vol. 14(3), pages 1-17, March.
    12. 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.
    13. 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.
    14. Manuel Gomes & Edmond S.-W. Ng & Richard Grieve & Richard Nixon & James Carpenter & Simon G. Thompson, 2012. "Developing Appropriate Methods for Cost-Effectiveness Analysis of Cluster Randomized Trials," Medical Decision Making, , vol. 32(2), pages 350-361, March.
    15. Mohamed El Alili & Johanna M. van Dongen & Jonas L. Esser & Martijn W. Heymans & Maurits W. van Tulder & Judith E. Bosmans, 2022. "A scoping review of statistical methods for trial‐based economic evaluations: The current state of play," Health Economics, John Wiley & Sons, Ltd., vol. 31(12), pages 2680-2699, December.
    16. Mohamed El Alili & Johanna M. Dongen & Keith S. Goldfeld & Martijn W. Heymans & Maurits W. Tulder & Judith E. Bosmans, 2020. "Taking the Analysis of Trial-Based Economic Evaluations to the Next Level: The Importance of Accounting for Clustering," PharmacoEconomics, Springer, vol. 38(11), pages 1247-1261, November.
    17. 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.
    18. 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.
    19. 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.
    20. 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.
    21. 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.
    22. 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, July.
    23. Borislava Mihaylova & Andrew Briggs & Anthony O'Hagan & Simon G. Thompson, 2011. "Review of statistical methods for analysing healthcare resources and costs," Health Economics, John Wiley & Sons, Ltd., vol. 20(8), pages 897-916, August.

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