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Multilevel models for estimating incremental net benefits in multinational studies

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  • Richard Grieve
  • Richard Nixon
  • Simon G. Thompson
  • John Cairns

Abstract

Multilevel models (MLMs) have been recommended for estimating incremental net benefits (INBs) in multicentre cost‐effectiveness analysis (CEA). However, these models have assumed that the INBs are exchangeable and that there is a common variance across all centres. This paper examines the plausibility of these assumptions by comparing various MLMs for estimating the mean INB in a multinational CEA. The results showed that the MLMs that assumed the INBs were exchangeable and had a common variance led to incorrect inferences. The MLMs that included covariates to allow for systematic differences across the centres, and estimated different variances in each centre, made more plausible assumptions, fitted the data better and led to more appropriate inferences. We conclude that the validity of assumptions underlying MLMs used in CEA need to be critically evaluated before reliable conclusions can be drawn. Copyright © 2006 John Wiley & Sons, Ltd.

Suggested Citation

  • 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, August.
  • Handle: RePEc:wly:hlthec:v:16:y:2007:i:8:p:815-826
    DOI: 10.1002/hec.1198
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    References listed on IDEAS

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    1. Richard Grieve & John Cairns & Simon G. Thompson, 2010. "Improving costing methods in multicentre economic evaluation: the use of multiple imputation for unit costs," Health Economics, John Wiley & Sons, Ltd., vol. 19(8), pages 939-954, August.
    2. Christian E. H. Boehler & Joanne Lord, 2016. "Mind the Gap! A Multilevel Analysis of Factors Related to Variation in Published Cost-Effectiveness Estimates within and between Countries," Medical Decision Making, , vol. 36(1), pages 31-47, January.
    3. Manuel Gomes & Richard Grieve & Richard Nixon & Edmond S.‐W. Ng & James Carpenter & Simon G. Thompson, 2012. "Methods For Covariate Adjustment In Cost‐Effectiveness Analysis That Use Cluster Randomised Trials," Health Economics, John Wiley & Sons, Ltd., vol. 21(9), pages 1101-1118, September.
    4. Manuel Gomes & Karla Díaz-Ordaz & Richard Grieve & Michael G. Kenward, 2013. "Multiple Imputation Methods for Handling Missing Data in Cost-effectiveness Analyses That Use Data from Hierarchical Studies," Medical Decision Making, , vol. 33(8), pages 1051-1063, November.
    5. Md Abu Manju & Math J. J. M. Candel & Gerard J. P. van Breukelen, 2019. "SamP2CeT: an interactive computer program for sample size and power calculation for two-level cost-effectiveness trials," Computational Statistics, Springer, vol. 34(1), pages 47-70, March.
    6. Louise B. Russell & Gyan Bhanot & Sun-Young Kim & Anushua Sinha, 2018. "Using Cluster Analysis to Group Countries for Cost-effectiveness Analysis: An Application to Sub-Saharan Africa," Medical Decision Making, , vol. 38(2), pages 139-149, February.
    7. 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.
    8. Aline Gauthier & Andrea Manca & Susan Anton, 2009. "Bayesian Modelling of Healthcare Resource Use in Multinational Randomized Clinical Trials," PharmacoEconomics, Springer, vol. 27(12), pages 1017-1029, December.
    9. Mohamed El Alili & Johanna M. van Dongen & Jonas L. Esser & Martijn W. Heymans & Maurits W. van Tulder & Judith E. Bosmans, 2022. "A scoping review of statistical methods for trial‐based economic evaluations: The current state of play," Health Economics, John Wiley & Sons, Ltd., vol. 31(12), pages 2680-2699, December.
    10. Laura Haas & Tom Stargardt & Jonas Schreyoegg, 2012. "Cost-effectiveness of open versus laparoscopic appendectomy: a multilevel approach with propensity score matching," The European Journal of Health Economics, Springer;Deutsche Gesellschaft für Gesundheitsökonomie (DGGÖ), vol. 13(5), pages 549-560, October.

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