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Regression methods for covariate adjustment and subgroup analysis for non-censored cost-effectiveness data

Author

Listed:
  • Andrew R. Willan
  • Andrew H. Briggs

    (Health Economics Research Centre, University of Oxford, UK)

  • Jeffrey S. Hoch

    (Department of Epidemiology and Biostatistics, University of Western Ontario, Canada)

Abstract

The current interest in undertaking cost-effectiveness analyses alongside clinical trials has lead to the increasing availability of patient-level data on both the costs and effectiveness of intervention. In a recent paper, we show how cost-effectiveness analysis can be undertaken in a regression framework. In the current paper we develop a direct regression approach to cost-effectiveness analysis by proposing the use of a system of seemingly unrelated regression equations to provide a more general method for prognostic factor adjustment with emphasis on sub-group analysis. This more general method can be used in either an incremental cost-effectiveness or an incremental net-benefit approach, and does not require that the set of independent variables for costs and effectiveness be the same. Furthermore, the method can exhibit efficiency gains over unrelated ordinary least squares regression. Copyright © 2003 John Wiley & Sons, Ltd.

Suggested Citation

  • Andrew R. Willan & Andrew H. Briggs & Jeffrey S. Hoch, 2004. "Regression methods for covariate adjustment and subgroup analysis for non-censored cost-effectiveness data," Health Economics, John Wiley & Sons, Ltd., vol. 13(5), pages 461-475.
  • Handle: RePEc:wly:hlthec:v:13:y:2004:i:5:p:461-475
    DOI: 10.1002/hec.843
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    References listed on IDEAS

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    1. Tambour, Magnus & Zethraeus, Niklas & Johannesson, Magnus, 1997. "A Note on Confidence Intervals in Cost-Effectiveness Analysis," SSE/EFI Working Paper Series in Economics and Finance 181, Stockholm School of Economics.
    2. Daniel Polsky & Henry A. Glick & Richard Willke & Kevin Schulman, 1997. "Confidence Intervals for Cost-Effectiveness Ratios: A Comparison of Four Methods," Health Economics, John Wiley & Sons, Ltd., vol. 6(3), pages 243-252.
    3. Daniel F. Heitjan, 2000. "Fieller's method and net health benefits," Health Economics, John Wiley & Sons, Ltd., vol. 9(4), pages 327-335.
    4. Andre Ament & Rob Baltussen, 1997. "The Interpretation of results of economic evaluation: explicating the value of health," Health Economics, John Wiley & Sons, Ltd., vol. 6(6), pages 625-635.
    5. Andrew H. Briggs & David E. Wonderling & Christopher Z. Mooney, 1997. "Pulling cost-effectiveness analysis up by its bootstraps: A non-parametric approach to confidence interval estimation," Health Economics, John Wiley & Sons, Ltd., vol. 6(4), pages 327-340.
    6. Jeffrey S. Hoch & Andrew H. Briggs & Andrew R. Willan, 2002. "Something old, something new, something borrowed, something blue: a framework for the marriage of health econometrics and cost-effectiveness analysis," Health Economics, John Wiley & Sons, Ltd., vol. 11(5), pages 415-430.
    7. Andrew Briggs & Paul Fenn, 1998. "Confidence intervals or surfaces? Uncertainty on the cost-effectiveness plane," Health Economics, John Wiley & Sons, Ltd., vol. 7(8), pages 723-740.
    8. Andrew H. Briggs, 1999. "A Bayesian approach to stochastic cost-effectiveness analysis," Health Economics, John Wiley & Sons, Ltd., vol. 8(3), pages 257-261.
    9. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

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    Cited by:

    1. Moreno, E. & Girón, F.J. & Martínez, M.L. & Vázquez-Polo, F.J. & Negrín, M.A., 2013. "Optimal treatments in cost-effectiveness analysis in the presence of covariates: Improving patient subgroup definition," European Journal of Operational Research, Elsevier, vol. 226(1), pages 173-182.
    2. Negri­n, Miguel A. & Vázquez-Polo, Francisco-José, 2008. "Incorporating model uncertainty in cost-effectiveness analysis: A Bayesian model averaging approach," Journal of Health Economics, Elsevier, vol. 27(5), pages 1250-1259, September.
    3. Moreno, Elías & Girón, F.J. & Vázquez-Polo, F.J. & Negrín, M.A., 2012. "Optimal healthcare decisions: The importance of the covariates in cost–effectiveness analysis," European Journal of Operational Research, Elsevier, vol. 218(2), pages 512-522.
    4. repec:spr:pharmo:v:1:y:2017:i:3:d:10.1007_s41669-017-0023-6 is not listed on IDEAS
    5. Rita Faria & Manuel Gomes & David Epstein & Ian White, 2014. "A Guide to Handling Missing Data in Cost-Effectiveness Analysis Conducted Within Randomised Controlled Trials," PharmacoEconomics, Springer, vol. 32(12), pages 1157-1170, December.
    6. Jeffrey Hoch & Carolyn Dewa, 2007. "Lessons from Trial-Based Cost-Effectiveness Analyses of Mental Health Interventions," PharmacoEconomics, Springer, vol. 25(10), pages 807-816, October.
    7. repec:spr:pharme:v:35:y:2017:i:7:d:10.1007_s40273-017-0505-5 is not listed on IDEAS
    8. Francisco-José Polo & Miguel Negrín & Xavier Badía & Montse Roset, 2005. "Bayesian regression models for cost-effectiveness analysis," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 6(1), pages 45-52, March.
    9. Andrew Briggs, 2012. "Statistical Methods for Cost-effectiveness Analysis Alongside Clinical Trials," Chapters,in: The Elgar Companion to Health Economics, Second Edition, chapter 50 Edward Elgar Publishing.
    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.
    11. repec:spr:aphecp:v:15:y:2017:i:3:d:10.1007_s40258-016-0298-2 is not listed on IDEAS
    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. Richard Grieve & Richard Nixon & Simon G. Thompson & John Cairns, 2007. "Multilevel models for estimating incremental net benefits in multinational studies," Health Economics, John Wiley & Sons, Ltd., vol. 16(8), pages 815-826.
    14. Andrea Manca & Neil Hawkins & Mark J. Sculpher, 2005. "Estimating mean QALYs in trial-based cost-effectiveness analysis: the importance of controlling for baseline utility," Health Economics, John Wiley & Sons, Ltd., vol. 14(5), pages 487-496.
    15. Richard M. Nixon & Simon G. Thompson, 2005. "Methods for incorporating covariate adjustment, subgroup analysis and between-centre differences into cost-effectiveness evaluations," Health Economics, John Wiley & Sons, Ltd., vol. 14(12), pages 1217-1229.
    16. Rachael Hunter & Gianluca Baio & Thomas Butt & Stephen Morris & Jeff Round & Nick Freemantle, 2015. "An Educational Review of the Statistical Issues in Analysing Utility Data for Cost-Utility Analysis," PharmacoEconomics, Springer, vol. 33(4), pages 355-366, April.
    17. 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.

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