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Parametric modelling of cost data: some simulation evidence

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  • Andrew Briggs
  • Richard Nixon
  • Simon Dixon
  • Simon Thompson

Abstract

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, April.
    • 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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    1. John Mullahy, 1998. "Much Ado About Two: Reconsidering Retransformation and the Two-Part Model in Health Economics," NBER Technical Working Papers 0228, National Bureau of Economic Research, Inc.
    2. Marks R. Nester, 1996. "An Applied Statistician's Creed," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 45(4), pages 401-410, December.
    3. Duan, Naihua, et al, 1983. "A Comparison of Alternative Models for the Demand for Medical Care," Journal of Business & Economic Statistics, American Statistical Association, vol. 1(2), pages 115-126, April.
    4. Manning, Willard G, et al, 1987. "Health Insurance and the Demand for Medical Care: Evidence from a Randomized Experiment," American Economic Review, American Economic Association, vol. 77(3), pages 251-277, June.
    5. Mullahy, John, 1998. "Much ado about two: reconsidering retransformation and the two-part model in health econometrics," Journal of Health Economics, Elsevier, vol. 17(3), pages 247-281, June.
    6. Partha Deb & James F. Burgess, Jr., 2003. "A Quasi-experimental Comparison of Econometric Models for Health Care Expenditures," Economics Working Paper Archive at Hunter College 212, Hunter College Department of Economics.
    7. Zhou, Xiao-Hua & Tu, Wanzhu, 2000. "Interval estimation for the ratio in means of log-normally distributed medical costs with zero values," Computational Statistics & Data Analysis, Elsevier, vol. 35(2), pages 201-210, December.
    8. Manning, Willard G. & Mullahy, John, 2001. "Estimating log models: to transform or not to transform?," Journal of Health Economics, Elsevier, vol. 20(4), pages 461-494, July.
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    Cited by:

    1. Andrew R. Willan & Simon Eckermann, 2012. "Accounting For Between‐Study Variation In Incremental Net Benefit In Value Of Information Methodology," Health Economics, John Wiley & Sons, Ltd., vol. 21(10), pages 1183-1195, October.
    2. Edward C. F. Wilson & Miranda Mugford & Garry Barton & Lee Shepstone, 2016. "Efficient Research Design," Medical Decision Making, , vol. 36(3), pages 335-348, April.
    3. Andrew Willan, 2011. "Sample Size Determination for Cost-Effectiveness Trials," PharmacoEconomics, Springer, vol. 29(11), pages 933-949, November.
    4. Jasjeet Singh Sekhon & Richard D. Grieve, 2012. "A matching method for improving covariate balance in cost‐effectiveness analyses," Health Economics, John Wiley & Sons, Ltd., vol. 21(6), pages 695-714, June.
    5. 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.
    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. 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.
    8. 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.
    9. 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.
    10. 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.
    11. 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.
    12. C. Elizabeth McCarron & Eleanor M. Pullenayegum & Lehana Thabane & Ron Goeree & Jean-Eric Tarride, 2013. "The Impact of Using Informative Priors in a Bayesian Cost-Effectiveness Analysis," Medical Decision Making, , vol. 33(3), pages 437-450, April.
    13. 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.
    14. 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, January.
    15. 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.
    16. 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.
    17. Zhao, Xiaobing & Zhou, Xian, 2009. "Semiparametric modeling of medical cost data containing zeros," Statistics & Probability Letters, Elsevier, vol. 79(9), pages 1207-1214, May.
    18. Claudia Geue & James Lewsey & Paula Lorgelly & Lindsay Govan & Carole Hart & Andrew Briggs, 2012. "Spoilt For Choice: Implications Of Using Alternative Methods Of Costing Hospital Episode Statistics," Health Economics, John Wiley & Sons, Ltd., vol. 21(10), pages 1201-1216, October.
    19. 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.
    20. 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.
    21. 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.
    22. 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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