Journal ArticleDOI
Generalized linear mixed models for meta‐analysis
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TLDR
In this paper, the authors examined two strategies for meta-analysis of a series of 2 x 2 tables with the odds ratio modelled as a linear combination of study level covariates and random effects representing between-study variation.Abstract:
We examine two strategies for meta-analysis of a series of 2 x 2 tables with the odds ratio modelled as a linear combination of study level covariates and random effects representing between-study variation. Penalized quasi-likelihood (PQL), an approximate inference technique for generalized linear mixed models, and a linear model fitted by weighted least squares to the observed log-odds ratios are used to estimate regression coefficients and dispersion parameters. Simulation results demonstrate that both methods perform adequate approximate inference under many conditions, but that neither method works well in the presence of highly sparse data. Under certain conditions with small cell frequencies the PQL method provides better inference.read more
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Advanced methods in meta-analysis: multivariate approach and meta-regression.
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The binomial distribution of meta-analysis was preferred to model within-study variability.
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Reference EntryDOI
Biologics for rheumatoid arthritis: an overview of Cochrane reviews
Jasvinder A. Singh,Robin Christensen,George A. Wells,Maria E. Suarez-Almazor,Rachelle Buchbinder,Maria A. Lopez-Olivo,Elizabeth Tanjong Ghogomu,Peter Tugwell +7 more
TL;DR: Anakinra seemed less efficacious than etanercept, adalimumab and rituximab and etanerscept and seemed to cause fewer withdrawals due to adverse events than ad alimumab, anakinra and infliximab, however there is a lack of head-to-head comparison studies.
References
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Journal ArticleDOI
Meta-Analysis in Clinical Trials*
TL;DR: This paper examines eight published reviews each reporting results from several related trials in order to evaluate the efficacy of a certain treatment for a specified medical condition and suggests a simple noniterative procedure for characterizing the distribution of treatment effects in a series of studies.
Journal ArticleDOI
Approximate inference in generalized linear mixed models
Norman E. Breslow,D. G. Clayton +1 more
TL;DR: In this paper, generalized linear mixed models (GLMM) are used to estimate the marginal quasi-likelihood for the mean parameters and the conditional variance for the variances, and the dispersion matrix is specified in terms of a rank deficient inverse covariance matrix.
Journal ArticleDOI
Parametric Empirical Bayes Inference: Theory and Applications
TL;DR: In this paper, a review of the state of the art in multiparameter shrinkage estimators with emphasis on the empirical Bayes viewpoint, particularly in the case of parametric prior distributions, is presented.
Journal ArticleDOI
Generalized linear mixed models a pseudo-likelihood approach
TL;DR: In this article, a pseudo-likelihood estimation procedure is developed to fit this class of mixed models based on an approximate marginal model for the mean response, implemented via iterated fitting of a weighted Gaussian linear mixed model to a modified dependent variable.
Journal ArticleDOI
A random-effects regression model for meta-analysis
TL;DR: The random-effects regression method performs well in the context of a meta-analysis of the efficacy of a vaccine for the prevention of tuberculosis, where certain factors are thought to modify vaccine efficacy.