van Houwelingen Hans C, Arends Lidia R, Stijnen Theo
Department of Medical Statistics, Leiden University Medical Center, P.O. Box 9604, 2300 RC Leiden, The Netherlands.
Stat Med. 2002 Feb 28;21(4):589-624. doi: 10.1002/sim.1040.
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 fitted using SAS Proc Mixed.
本关于元分析高级统计方法的教程可视为诺曼德近期发表在《生物统计学教程》上关于元分析的基础方法教程的续篇。在使用近似似然的一般线性混合模型框架内，我们讨论了元分析中分析单变量和双变量治疗效果的方法以及元回归方法。还讨论了模型的几种扩展，如精确似然、非正态混合和多个终点。最后我们讨论了贝叶斯方法在元分析中的应用。所有方法均通过一项关于卡介苗预防结核病疗效的元分析进行说明。所有使用近似似然的分析都可以通过标准软件进行。我们展示了如何使用SAS Proc Mixed拟合模型。
