Advances in the meta-analysis of heterogeneous clinical trials I: the inverse variance heterogeneity model

Doi, Suhail A.R., Barendregt, Jan J., Khan, Shahjahan, Thalib, Lukman and Williams, Gail M. (2015) Advances in the meta-analysis of heterogeneous clinical trials I: the inverse variance heterogeneity model. Contemporary Clinical Trials, 45 130-138. doi:10.1016/j.cct.2015.05.009

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Author Doi, Suhail A.R.
Barendregt, Jan J.
Khan, Shahjahan
Thalib, Lukman
Williams, Gail M.
Title Advances in the meta-analysis of heterogeneous clinical trials I: the inverse variance heterogeneity model
Journal name Contemporary Clinical Trials   Check publisher's open access policy
ISSN 1559-2030
1551-7144
Publication date 2015-11
Sub-type Article (original research)
DOI 10.1016/j.cct.2015.05.009
Open Access Status File (Author Post-print)
Volume 45
Start page 130
End page 138
Total pages 9
Place of publication Philadelphia, PA, United States
Publisher Elsevier
Collection year 2016
Language eng
Abstract This article examines an improved alternative to the random effects (RE) model for meta-analysis of heterogeneous studies. It is shown that the known issues of underestimation of the statistical error and spuriously overconfident estimates with the RE model can be resolved by the use of an estimator under the fixed effect model assumption with a quasi-likelihood based variance structure — the IVhet model. Extensive simulations confirm that this estimator retains a correct coverage probability and a lower observed variance than the RE model estimator, regardless of heterogeneity. When the proposed IVhet method is applied to the controversial meta-analysis of intravenous magnesium for the prevention of mortality after myocardial infarction, the pooled OR is 1.01 (95% CI 0.71–1.46) which not only favors the larger studies but also indicates more uncertainty around the point estimate. In comparison, under the RE model the pooled OR is 0.71 (95% CI 0.57–0.89) which, given the simulation results, reflects underestimation of the statistical error. Given the compelling evidence generated, we recommend that the IVhet model replace both the FE and RE models. To facilitate this, it has been implemented into free meta-analysis software called MetaXL which can be downloaded from www.epigear.com.
Keyword Fixed effect
Heterogeneity
Meta-analysis
Quasi-likelihood
Random effects
Q-Index Code C1
Q-Index Status Confirmed Code
Institutional Status UQ

Document type: Journal Article
Sub-type: Article (original research)
Collections: Official 2016 Collection
School of Public Health Publications
 
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