Simple pooling versus combining in meta-analysis
Simple pooling versus combining in meta-analysis
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DOI：
10.1177/01632780122034885
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发表时间：
2001-06-01
影响因子：
2.9
通讯作者：
Olkin, I
中科院分区：
文献类型：
--
作者：
Bravata, DM;Olkin, I
简单的数据汇集通常用于提供子组数据或来自许多相关研究的数据的总体摘要。在简单池化中，数据被合并而不被加权，因此，进行分析时就好像数据来自单个样本一样。这种分析忽略了汇总的亚组或个体研究的特征，可能产生虚假或反直觉的结果。在荟萃分析中，来自亚组或单个研究的数据首先加权，然后合并，从而避免了简单合并的一些问题。本文的目的是描述简单池化与元分析的不同之处，详细分析为什么简单池化可能是一个糟糕的过程，并表明通过元分析方法的结合可以避免这些问题。
The simple pooling of data is often used to provide an overall summary of subgroup data or data from a number of related studies. In simple pooling, data are combined without being weighted Therefore, the analysis is performed as if the data were derived from a single sample. This kind of analysis ignores characteristics of the subgroups or individual studies being pooled and can yield spurious or counter intuitive results. In meta-analysis, data from subgroups or individual studies are weighted first, then combined, thereby avoiding some of the problems of simple pooling. The purpose of this article is to describe how simple pooling differs from meta-analysis, provide a detailed analysis of why simple pooling can be a poor procedure, and show that combining by meta-analytic methods avoids such problems.