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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.

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Advanced methods in meta-analysis: multivariate approach and meta-regression.

TL;DR: This tutorial on advanced statistical methods for meta-analysis can be seen as a sequel to the recent Tutorial in Biostatistics on meta- analysis by Normand, which focused on elementary methods.
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Fixed or random effects meta-analysis? Common methodological issues in systematic reviews of effectiveness.

TL;DR: Some of the common methodological issues that arise when conducting systematic reviews and meta-analyses of effectiveness data are discussed, including issues related to study designs, meta-analysis, and the use and interpretation of effect sizes.
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Do Patients Drop Out Prematurely from Exposure Therapy for PTSD

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The binomial distribution of meta-analysis was preferred to model within-study variability.

TL;DR: The exact likelihood approach is the method of preference and should be used whenever feasible because it performs always better than the approximate approach and gives unbiased estimates.
Reference EntryDOI

Biologics for rheumatoid arthritis: an overview of Cochrane reviews

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

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.
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