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荟萃分析与证据综合

Meta-analysis and the synthesis of evidence.

作者信息

Abrams K, Jones D R

机构信息

Department of Epidemiology and Public Health, University of Leicester, UK.

出版信息

IMA J Math Appl Med Biol. 1995 Sep-Dec;12(3-4):297-313. doi: 10.1093/imammb/12.3-4.297.

Abstract

Use of meta-analytical (quantitative overview) techniques is now commonplace in a large range of medical-research contexts, with a rapid rise in its frequency of use being particularly apparent in the last decade. Many methods of meta-analysis have been proposed and used, from crude 'vote-counting' of studies showing significant or nonsignificant results, through methods for combination of effect-size estimates based on fixed- or random-effects models, to general, linear, mixed models and Bayesian methods. The history of meta-analysis and the advantages and disadvantages of various approaches to it are briefly reviewed in this paper, with reference to its application in health-services research and related fields. Broader approaches to the synthesis of evidence in these contexts using conventional multilevel modelling and hierarchical Bayesian models to address the combination of evidence from disparate types of study are then outlined.

摘要

在大量医学研究背景下,使用荟萃分析(定量综述)技术如今已很常见,在过去十年中其使用频率的快速上升尤为明显。已经提出并使用了许多荟萃分析方法,从对显示显著或不显著结果的研究进行粗略的“投票计数”,到基于固定效应或随机效应模型的效应量估计合并方法,再到通用线性混合模型和贝叶斯方法。本文简要回顾了荟萃分析的历史以及各种方法的优缺点,并提及了其在卫生服务研究及相关领域的应用。接着概述了在这些背景下使用传统多层次建模和分层贝叶斯模型来综合证据的更广泛方法,以解决来自不同类型研究的证据合并问题。

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