IDEAS home Printed from https://ideas.repec.org/a/taf/japsta/v40y2013i2p298-310.html
   My bibliography  Save this article

Modeling healthcare costs in simultaneous presence of asymmetry, heteroscedasticity and correlation

Author

Listed:
  • Ileana Baldi
  • Eva Pagano
  • Paola Berchialla
  • Alessandro Desideri
  • Alberto Ferrando
  • Franco Merletti
  • Dario Gregori

Abstract

Highly skewed outcome distributions observed across clusters are common in medical research. The aim of this paper is to understand how regression models widely used for accommodating asymmetry fit clustered data under heteroscedasticity. In a simulation study, we provide evidence on the performance of the Gamma Generalized Linear Mixed Model (GLMM) and log-Linear Mixed-Effect (LME) model under a variety of data-generating mechanisms. Two case studies from health expenditures literature, the cost of strategies after myocardial infarction randomized clinical trial on the cost of strategies after myocardial infarction and the European Pressure Ulcer Advisory Panel hospital prevalence survey of pressure ulcers, are analyzed and discussed. According to simulation results, the log-LME model for a Gamma response can lead to estimations that are biased by as much as 10% of the true value, depending on the error variance. In the Gamma GLMM, the bias never exceeds 1%, regardless of the extent of heteroscedasticity, and the confidence intervals perform as nominally stated under most conditions. The Gamma GLMM with a log link seems to be more robust to both Gamma and log-normal generating mechanisms than the log-LME model.

Suggested Citation

  • Ileana Baldi & Eva Pagano & Paola Berchialla & Alessandro Desideri & Alberto Ferrando & Franco Merletti & Dario Gregori, 2013. "Modeling healthcare costs in simultaneous presence of asymmetry, heteroscedasticity and correlation," Journal of Applied Statistics, Taylor & Francis Journals, vol. 40(2), pages 298-310, February.
    • Handle: RePEc:taf:japsta:v:40:y:2013:i:2:p:298-310
    DOI: 10.1080/02664763.2012.740628
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1080/02664763.2012.740628
    Download Restriction: Access to full text is restricted to subscribers.
    File URL: https://libkey.io/10.1080/02664763.2012.740628?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Manning, W. G. & Duan, N. & Rogers, W. H., 1987. "Monte Carlo evidence on the choice between sample selection and two-part models," Journal of Econometrics, Elsevier, vol. 35(1), pages 59-82, May.
    2. Richard Grieve & Richard Nixon & Simon G. Thompson & Charles Normand, 2005. "Using multilevel models for assessing the variability of multinational resource use and cost data," Health Economics, John Wiley & Sons, Ltd., vol. 14(2), pages 185-196, February.
    3. Anirban Basu & Willard G. Manning & John Mullahy, 2004. "Comparing alternative models: log vs Cox proportional hazard?," Health Economics, John Wiley & Sons, Ltd., vol. 13(8), pages 749-765, August.
    4. Nigel Rice & Andrew Jones, 1997. "Multilevel models and health economics," Health Economics, John Wiley & Sons, Ltd., vol. 6(6), pages 561-575, November.
    5. Manning, Willard G., 1998. "The logged dependent variable, heteroscedasticity, and the retransformation problem," Journal of Health Economics, Elsevier, vol. 17(3), pages 283-295, June.
    6. 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.
    7. Daowen Zhang & Marie Davidian, 2001. "Linear Mixed Models with Flexible Distributions of Random Effects for Longitudinal Data," Biometrics, The International Biometric Society, vol. 57(3), pages 795-802, September.
    8. Ai, Chunrong & Norton, Edward C., 2000. "Standard errors for the retransformation problem with heteroscedasticity," Journal of Health Economics, Elsevier, vol. 19(5), pages 697-718, September.
    9. Matthew J. Gurka & Lloyd J. Edwards & Keith E. Muller & Lawrence L. Kupper, 2006. "Extending the Box–Cox transformation to the linear mixed model," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 169(2), pages 273-288, March.
    10. 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.
    11. Kathleen Carey, 2000. "A multilevel modelling approach to analysis of patient costs under managed care," Health Economics, John Wiley & Sons, Ltd., vol. 9(5), pages 435-446, July.
    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. Besstremyannaya, Galina, 2017. "Measuring income equity in the demand for healthcare with finite mixture models," Applied Econometrics, Russian Presidential Academy of National Economy and Public Administration (RANEPA), vol. 46, pages 5-29.
    2. Galina Besstremyannaya, 2014. "Heterogeneous effect of coinsurance rate on healthcare costs: generalized finite mixtures and matching estimators," Discussion Papers 14-014, Stanford Institute for Economic Policy Research.

    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. 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.
    2. 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.
    3. Stargardt, Tom & Schreyögg, Jonas, 2012. "A framework to evaluate the effects of small area variations in healthcare infrastructure on diagnostics and patient outcomes of rare diseases based on administrative data," Health Policy, Elsevier, vol. 105(2), pages 110-118.
    4. Manning, Willard G. & Basu, Anirban & Mullahy, John, 2005. "Generalized modeling approaches to risk adjustment of skewed outcomes data," Journal of Health Economics, Elsevier, vol. 24(3), pages 465-488, May.
    5. 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.
    6. Yves Staudt & Joël Wagner, 2021. "Assessing the Performance of Random Forests for Modeling Claim Severity in Collision Car Insurance," Risks, MDPI, vol. 9(3), pages 1-28, March.
    7. Hao Yu, 2017. "China’s medical savings accounts: an analysis of the price elasticity of demand for health care," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 18(6), pages 773-785, July.
    8. John Mullahy, 2015. "In Memoriam: Willard G. Manning, 1946‐2014," Health Economics, John Wiley & Sons, Ltd., vol. 24(3), pages 253-257, March.
    9. Jonas Schreyögg & Tom Stargardt & Oliver Tiemann, 2011. "Costs and quality of hospitals in different health care systems: a multi‐level approach with propensity score matching," Health Economics, John Wiley & Sons, Ltd., vol. 20(1), pages 85-100, January.
    10. Manos Matsaganis & Theodore Mitrakos & Panos Tsakloglou, 2008. "Modelling Household Expenditure on Health Care in Greece," Working Papers 68, Bank of Greece.
    11. Jones, A. & Lomas, J. & Rice, N., 2014. "Going Beyond the Mean in Healthcare Cost Regressions: a Comparison of Methods for Estimating the Full Conditional Distribution," Health, Econometrics and Data Group (HEDG) Working Papers 14/26, HEDG, c/o Department of Economics, University of York.
    12. Meyerhoefer, Chad D. & Pylypchuk, Vuriy, 2008. "AJAE Appendix: Does Participation in the Food Stamp Program Increase the Prevalence of Obesity and Health Care Spending?," American Journal of Agricultural Economics APPENDICES, Agricultural and Applied Economics Association, vol. 90(2), pages 1-6.
    13. Brigitte Dormont & Hélène Huber, 2006. "Ageing and changes in medical practices : reassessing theinfluence of demography," Post-Print halshs-00274723, HAL.
    14. Gospodinov, Nikolay & Irvine, Ian, 2009. "Tobacco taxes and regressivity," Journal of Health Economics, Elsevier, vol. 28(2), pages 375-384, March.
    15. Jeonghoon Ahn, 2004. "Panel Data Sample Selection Model: an Application to Employee Choice of Health Plan Type and Medical Cost Estimation," Econometric Society 2004 Far Eastern Meetings 560, Econometric Society.
    16. Patrick Richard & Regine Walker & Pierre Alexandre, 2018. "The burden of out of pocket costs and medical debt faced by households with chronic health conditions in the United States," PLOS ONE, Public Library of Science, vol. 13(6), pages 1-13, June.
    17. Trottmann, Maria & Zweifel, Peter & Beck, Konstantin, 2012. "Supply-side and demand-side cost sharing in deregulated social health insurance: Which is more effective?," Journal of Health Economics, Elsevier, vol. 31(1), pages 231-242.
    18. Noémi Kreif & Richard Grieve & M. Zia Sadique, 2013. "Statistical Methods For Cost‐Effectiveness Analyses That Use Observational Data: A Critical Appraisal Tool And Review Of Current Practice," Health Economics, John Wiley & Sons, Ltd., vol. 22(4), pages 486-500, April.
    19. Buntin, Melinda Beeuwkes & Zaslavsky, Alan M., 2004. "Too much ado about two-part models and transformation?: Comparing methods of modeling Medicare expenditures," Journal of Health Economics, Elsevier, vol. 23(3), pages 525-542, May.
    20. Keith Davis & Timothy Bell & Jacqueline Miller & Derek Misurski & Bela Bapat, 2011. "Hospital costs, length of stay and mortality associated with childhood, adolescent and young Adult meningococcal disease in the US," Applied Health Economics and Health Policy, Springer, vol. 9(3), pages 197-207, May.

    More about this item

    Statistics

    Access and download statistics

    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:taf:japsta:v:40:y:2013:i:2:p:298-310. 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: Chris Longhurst (email available below). General contact details of provider: http://www.tandfonline.com/CJAS20 .

    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.