Simple heterogeneity variance estimation for meta-analysis
Simple heterogeneity variance estimation for meta-analysis
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DOI：
10.1111/j.1467-9876.2005.00489.x
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发表时间：
2005-01-01
影响因子：
1.6
通讯作者：
Jonkman, JN
中科院分区：
文献类型：
--
作者：
Sidik, K;Jonkman, JN
本文提出了一种估计随机效应模型中异质性方差的简单方法。所提出的估计量是简单的，易于计算，并具有改善的偏差相比，最常见的估计用于随机效应荟萃分析，特别是当异质性方差是中等偏大。此外，它总是产生一个非负估计的异质性方差，不像一些现有的估计。我们发现，基于这种异质性方差估计的总体效果的随机效应推断比使用共同估计的推断更可靠，在区间估计的覆盖概率方面。
A simple method of estimating the heterogeneity variance in a random-effects model for meta-analysis is proposed. The estimator that is presented is simple and easy to calculate and has improved bias compared with the most common estimator used in random-effects meta-analysis, particularly when the heterogeneity variance is moderate to large. In addition, it always yields a non-negative estimate of the heterogeneity variance, unlike some existing estimators. We find that random-effects inference about the overall effect based on this heterogeneity variance estimator is more reliable than inference using the common estimator, in terms of coverage probability for an interval estimate.