Sidik Kurex, Jonkman Jeffrey N
Bristol-Myers Squibb Company, Princeton, NJ, USA.
Department of Mathematics and Statistics, Grinnell College, Grinnell, IA, USA.
Biom J. 2022 Mar;64(3):598-616. doi: 10.1002/bimj.202000222. Epub 2021 Dec 11.
The between-study variance or heterogeneity variance is an important parameter in random effects meta-analysis. This paper uses an M-estimation framework to introduce and discuss variance estimators for quantifying the uncertainty in estimates of the heterogeneity variance using the noniterative generalized method of moments estimator and some related method of moments estimators. An example is used to further illustrate the variance estimators, and simulation results are presented for assessing the empirical properties of the proposed variance estimators.
研究间方差或异质性方差是随机效应荟萃分析中的一个重要参数。本文使用M估计框架来引入和讨论方差估计量，这些估计量用于使用非迭代广义矩估计量和一些相关的矩估计方法来量化异质性方差估计中的不确定性。通过一个例子进一步说明方差估计量，并给出模拟结果以评估所提出的方差估计量的经验性质。
