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Multivariate generalised linear mixed-effects models for the analysis of clinical trial-based cost-effectiveness data

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Achana, Felix A., Gallacher, Daniel C., Oppong, Raymond, Kim, Sungwook, Petrou, Stavros, Mason, James and Crowther, Michael (2021) Multivariate generalised linear mixed-effects models for the analysis of clinical trial-based cost-effectiveness data. Medical Decision Making, 41 (6). pp. 667-684. doi:10.1177/0272989X211003880

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Official URL: https://doi.org/10.1177/0272989X211003880

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Abstract

Economic evaluations conducted alongside randomized controlled trials are a popular vehicle for generating high-quality evidence on the incremental cost-effectiveness of competing health care interventions. Typically, in these studies, resource use (and by extension, economic costs) and clinical (or preference-based health) outcomes data are collected prospectively for trial participants to estimate the joint distribution of incremental costs and incremental benefits associated with the intervention. In this article, we extend the generalized linear mixed-model framework to enable simultaneous modeling of multiple outcomes of mixed data types, such as those typically encountered in trial-based economic evaluations, taking into account correlation of outcomes due to repeated measurements on the same individual and other clustering effects. We provide new wrapper functions to estimate the models in Stata and R by maximum and restricted maximum quasi-likelihood and compare the performance of the new routines with alternative implementations across a range of statistical programming packages. Empirical applications using observed and simulated data from clinical trials suggest that the new methods produce broadly similar results as compared with Stata’s merlin and gsem commands and a Bayesian implementation in WinBUGS. We highlight that, although these empirical applications primarily focus on trial-based economic evaluations, the new methods presented can be generalized to other health economic investigations characterized by multivariate hierarchical data structures.

Item Type: Journal Article
Subjects: R Medicine > RC Internal medicine
Divisions: Faculty of Medicine > Warwick Medical School
Library of Congress Subject Headings (LCSH): Clinical trials, Clinical trials -- Cost effectiveness
Journal or Publication Title: Medical Decision Making
Publisher: Sage Publications, Inc.
ISSN: 0272-989X
Official Date: 1 August 2021
Dates:
DateEvent
1 August 2021Published
5 April 2021Available
21 January 2021Accepted
Volume: 41
Number: 6
Page Range: pp. 667-684
DOI: 10.1177/0272989X211003880
Status: Peer Reviewed
Publication Status: Published
Access rights to Published version: Open Access
RIOXX Funder/Project Grant:
Project/Grant IDRIOXX Funder NameFunder ID
UNSPECIFIEDUniversity of Warwickhttp://dx.doi.org/10.13039/501100000741
UNSPECIFIEDNuffield College, University of Oxfordhttp://dx.doi.org/10.13039/501100000666
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