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Parametric modelling of cost data: some simulation evidence


  • Andrew Briggs

    (University of Oxford, UK)

  • Richard Nixon

    (MRC Biostatistics Unit, Cambridge, UK)

  • Simon Dixon

    (University of Sheffield, UK)

  • Simon Thompson

    (MRC Biostatistics Unit, Cambridge, UK)


Recently, commentators have suggested that the distributional form of cost data should be explicitly modelled to gain efficiency in estimating the population mean. We perform a series of simulation experiments to evaluate the usual sample mean and the mean estimator of a lognormal distribution, in the context of both theoretical distributions and three large empirical datasets. The sample mean is always unbiased, but is somewhat less efficient when the population distribution is truly lognormal. However the lognormal estimator can perform appallingly when the true distribution is not lognormal. In practical situations, where the true distribution is unknown, the sample mean generally remains the estimator of choice, especially when limited sample size prohibits detailed modelling of the cost data distribution. Copyright © 2005 John Wiley & Sons, Ltd.

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  • Andrew Briggs & Richard Nixon & Simon Dixon & Simon Thompson, 2005. "Parametric modelling of cost data: some simulation evidence," Health Economics, John Wiley & Sons, Ltd., vol. 14(4), pages 421-428.
  • Handle: RePEc:wly:hlthec:v:14:y:2005:i:4:p:421-428 DOI: 10.1002/hec.941

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    References listed on IDEAS

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    Cited by:

    1. Andrew M. Jones & James Lomas & Nigel Rice, 2014. "Applying Beta‐Type Size Distributions To Healthcare Cost Regressions," Journal of Applied Econometrics, John Wiley & Sons, Ltd., vol. 29(4), pages 649-670, June.
    2. Zhao, Xiaobing & Zhou, Xian, 2012. "Estimation of medical costs by copula models with dynamic change of health status," Insurance: Mathematics and Economics, Elsevier, vol. 51(2), pages 480-491.
    3. Yuan, Jun & Ng, Szu Hui & Sou, Weng Sut, 2016. "Uncertainty quantification of CO2 emission reduction for maritime shipping," Energy Policy, Elsevier, vol. 88(C), pages 113-130.
    4. Andrew Willan, 2011. "Sample Size Determination for Cost-Effectiveness Trials," PharmacoEconomics, Springer, vol. 29(11), pages 933-949, November.
    5. Paul C. Lambert & Lucinda J. Billingham & Nicola J. Cooper & Alex J. Sutton & Keith R. Abrams, 2008. "Estimating the cost-effectiveness of an intervention in a clinical trial when partial cost information is available: a Bayesian approach," Health Economics, John Wiley & Sons, Ltd., vol. 17(1), pages 67-81.
    6. 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.
    7. Edmond S.-W. Ng & Richard Grieve & James R. Carpenter, 2013. "Two-stage nonparametric bootstrap sampling with shrinkage correction for clustered data," Stata Journal, StataCorp LP, vol. 13(1), pages 141-164, March.
    8. Zou, Guang Yong & Taleban, Julia & Huo, Cindy Y., 2009. "Confidence interval estimation for lognormal data with application to health economics," Computational Statistics & Data Analysis, Elsevier, vol. 53(11), pages 3755-3764, September.
    9. Zhao, Xiaobing & Zhou, Xian, 2009. "Semiparametric modeling of medical cost data containing zeros," Statistics & Probability Letters, Elsevier, vol. 79(9), pages 1207-1214, May.
    10. Jones, A.M, 2010. "Models For Health Care," Health, Econometrics and Data Group (HEDG) Working Papers 10/01, HEDG, c/o Department of Economics, University of York.
    11. 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.
    12. 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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