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

被引:1266
作者
van Houwelingen, HC
Arends, LR
Stijnen, T
机构
[1] Leiden Univ, Med Ctr, Dept Med Stat, NL-2300 RC Leiden, Netherlands
[2] Erasmus MC, Dept Epidemiol & Biostat, NL-3000 DR Rotterdam, Netherlands
关键词
meta-analysis; meta-regression; multivariate random effects models;
D O I
10.1002/sim.1040
中图分类号
Q [生物科学];
学科分类号
07 ; 0710 ; 09 ;
摘要
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. Within the framework of the general linear mixed model using approximate likelihood. we discuss methods to analyse univariate as well as bivariate treatment effects in meta-analyses as well as meta-regression methods. Several extensions of the models are discussed, like exact likelihood, non-normal mixtures and multiple endpoints. We end with a discussion about the use of Bayesian methods in meta-analysis. All methods are illustrated by a meta-analysis concerning the efficacy of BCG vaccine against tuberculosis. All analyses that use approximate likelihood can be carried out by standard software. We demonstrate how the models can be flitted using SAS Proc Mixed. Copyright (C) 2002 John Wiley Sons, Ltd.
引用
收藏
页码:589 / 624
页数:36
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