A bivariate approach to meta-analysis

Van Houwelingen, Hans C.; Zwinderman, Koos H.; Stijnen, Theo

doi:10.1002/sim.4780122405

Cited by 327Meta-analysis and systematic reviewsStatistical Methods in Clinical TrialsStatistical Methods and Bayesian Inference

A bivariate approach to meta-analysis

Van Houwelingen, Hans C., Zwinderman, Koos H., Stijnen, Theo·1993·Statistics in Medicine

DOI 10.1002/sim.4780122405

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Abstract

The usual meta-analysis of a sequence of randomized clinical trials only considers the difference between two treatments and produces a point estimate and a confidence interval for a parameter that measures this difference. The usual parameter is the log(odds ratio) linked to Mantel-Haenszel methodology. Inference is made either under the assumption of homogeneity or in a random effects model that takes account of heterogeneity between trials. This paper has two goals. The first is to present a likelihood based method for the estimation of the parameters in the random effects model, which avoids the use of approximating Normal distributions. The second goal is to extend this method to a bivariate random effects model, in which the effects in both groups are supposed random. In this way inference can be made about the relationship between improvement and baseline effect. The method is demonstrated by a meta-analysis dataset of Collins and Langman.

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NPML has been noted to be unstable and has not been widely adopted.
“However, NPML has been noted to be unstable (Van Houwelingen et al., 1993) and has not been widely adopted.”
From A Re-Evaluation of Random-Effects Meta-Analysis (2009) · cites this paper as Van Houwelingen et al., 1993
Unless a baseline model is correct, the estimated relative treatment effects will be biased.
“However, unless this model is correct, the estimated relative treatment effects will be biased.”
From Evidence Synthesis for Decision Making 2: A Generalized Linear Modeling Framework for Pairwise and Network Meta-analysis of Randomized Controlled Trials (2013) · cites this paper as [30]

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Authors: Van Houwelingen, H. C., Zwinderman, K. H., & Stijnen, T.
Affiliations: Erasmus University Rotterdam (NL)
ORCID: Stijnen, Theo
Venue: Statistics in Medicine
Publisher: Wiley
Published: 1993-12-30
Volume: 12
Issue: 24
Pages: 2273-2284
ISSN: 0277-6715 (ISSN-L)
1097-0258
DOI: 10.1002/sim.4780122405
OpenAlex: W2142540473
Cited by: 327
References: 7
Citations by year: 2026: 4 · 2025: 10 · 2024: 11 · 2023: 12 · 2022: 7 · 2021: 19 · 2020: 19 · 2019: 12 · 2018: 16 · 2017: 7 · 2016: 8 · 2015: 9 · 2014: 23 · 2013: 14 · 2012: 17
FWCI: 2.37
Type: journal article
Language: en
Open access: closed
Licence: onlinelibrary.wiley.com/termsAndConditions#vor (vor, 4669 d)
Locations: Statistics in Medicine (publishedVersion)
PubMed (publishedVersion)
Topics: Social Sciences › Decision Sciences › Statistics, Probability and Uncertainty › Meta-analysis and systematic reviews
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods in Clinical Trials
Physical Sciences › Mathematics › Statistics and Probability › Statistical Methods and Bayesian Inference
Keywords: bivariate random-effects model, meta-analysis, likelihood estimation, Mantel-Haenszel estimator, treatment effect heterogeneity, baseline effects, randomized controlled trials, odds ratio
MeSH terms: Analysis of Variance, Data Interpretation, Statistical, Histamine H2 Antagonists, Humans, Peptic Ulcer Hemorrhage, Meta-Analysis as Topic, Models, Statistical, Confidence Intervals, Likelihood Functions, Odds Ratio, Randomized Controlled Trials as Topic

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A bivariate approach to meta-analysis

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