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A random effects four-part model, with application to correlated medical costs

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  • Liu, Lei
  • Conaway, Mark R.
  • Knaus, William A.
  • Bergin, James D.

Abstract

In this paper we propose a four-part random effects model, with application to correlated medical cost data. Four joint equations are used to model respectively: (1) the probability of seeking medical treatment, (2) the probability of being hospitalized (conditional on seeking medical treatment), and the actual amount of (3) outpatient and (4) inpatient costs. Our model simultaneously takes account of the inter-temporal (or within-cluster) correlation of each patient and the cross-equation correlation of the four equations, by means of joint linear mixed models and generalized linear mixed models. The estimation is accomplished by the high-order Laplace approximation technique in Raudenbush et al. [Raudenbush, S.W., Yang, M., Yosef, M., 2000. Maximum likelihood for generalized linear models with nested random effects via high-order, multivariate Laplace approximation. Journal of Computational and Graphical Statistics 9, 141-157] and Olsen and Schafer [Olsen, M.K., Schafer, J.L., 2001. A two-part random effects model for semicontinuous longitudinal data. Journal of the American Statistical Association 96, 730-745]. Our model is used to analyze monthly medical costs of 1397 chronic heart failure patients from the clinical data repository (CDR) at the University of Virginia.

Suggested Citation

  • Liu, Lei & Conaway, Mark R. & Knaus, William A. & Bergin, James D., 2008. "A random effects four-part model, with application to correlated medical costs," Computational Statistics & Data Analysis, Elsevier, vol. 52(9), pages 4458-4473, May.
    • Handle: RePEc:eee:csdana:v:52:y:2008:i:9:p:4458-4473
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    1. Onur Başer & Joseph C. Gardiner & Cathy J. Bradley & Hüseyin Yüce & Charles Given, 2006. "Longitudinal analysis of censored medical cost data," Health Economics, John Wiley & Sons, Ltd., vol. 15(5), pages 513-525, May.
    2. Harvey Goldstein & Jon Rasbash, 1996. "Improved Approximations for Multilevel Models with Binary Responses," Journal of the Royal Statistical Society Series A, Royal Statistical Society, vol. 159(3), pages 505-513, May.
    3. 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.
    4. 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.
    5. Huang Y., 2002. "Calibration Regression of Censored Lifetime Medical Cost," Journal of the American Statistical Association, American Statistical Association, vol. 97, pages 318-327, March.
    6. Lei Liu & Robert A. Wolfe & Xuelin Huang, 2004. "Shared Frailty Models for Recurrent Events and a Terminal Event," Biometrics, The International Biometric Society, vol. 60(3), pages 747-756, September.
    7. Raikou, M. & McGuire, A., 2004. "Estimating medical care costs under conditions of censoring," Journal of Health Economics, Elsevier, vol. 23(3), pages 443-470, May.
    8. 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.
    9. D. Y. Lin, 2000. "Proportional Means Regression for Censored Medical Costs," Biometrics, The International Biometric Society, vol. 56(3), pages 775-778, September.
    10. Zhang, Min & Strawderman, Robert L. & Cowen, Mark E. & Wells, Martin T., 2006. "Bayesian Inference for a Two-Part Hierarchical Model: An Application to Profiling Providers in Managed Health Care," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 934-945, September.
    11. Baser, Onur & Gardiner, Joseph C & Bradley, Cathy J & Given, Charles W, 2004. "Estimation from Censored Medical Cost Data," MPRA Paper 102198, University Library of Munich, Germany.
    12. 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.
    13. Zhou, Xiao-Hua & Liang, Hua, 2006. "Semi-parametric single-index two-part regression models," Computational Statistics & Data Analysis, Elsevier, vol. 50(5), pages 1378-1390, March.
    14. Heejung Bang & Anastasios A. Tsiatis, 2002. "Median Regression with Censored Cost Data," Biometrics, The International Biometric Society, vol. 58(3), pages 643-649, September.
    15. 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.
    16. Xuelin Huang & Lei Liu, 2007. "A Joint Frailty Model for Survival and Gap Times Between Recurrent Events," Biometrics, The International Biometric Society, vol. 63(2), pages 389-397, June.
    17. 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.
    18. Blough, David K. & Madden, Carolyn W. & Hornbrook, Mark C., 1999. "Modeling risk using generalized linear models," Journal of Health Economics, Elsevier, vol. 18(2), pages 153-171, April.
    19. Robinson, John W. & Zeger, Scott L. & Forrest, Christopher B., 2006. "A Hierarchical Multivariate Two-Part Model for Profiling Providers' Effects on Health Care Charges," Journal of the American Statistical Association, American Statistical Association, vol. 101, pages 911-923, September.
    20. 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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    2. Arnab Mukherji & Satrajit Roychowdhury & Pulak Ghosh & Sarah Brown, 2012. "Estimating Healthcare Demand for an Aging Population: A Flexible and Robust Bayesian Joint Model," Working Papers 2012027, The University of Sheffield, Department of Economics.
    3. Qi Liu & Jin Liu & Shuntian Sui, 2020. "Public Medical Insurance and Healthcare Utilization and Expenditures of Older with Chronic Diseases in Rural China: Evidence from NRCMS," IJERPH, MDPI, vol. 17(20), pages 1-15, October.
    4. Lu Deng & Wendy Lou & Nicholas Mitsakakis, 2019. "Modeling right-censored medical cost data in regression and the effects of covariates," Statistical Methods & Applications, Springer;Società Italiana di Statistica, vol. 28(1), pages 143-155, March.

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