Fixed effects and variance components estimation in three-level meta-analysis
Fixed effects and variance components estimation in three-level meta-analysis
复制标题
DOI：
10.1002/jrsm.35
复制
发表时间：
2011-03-01
影响因子：
9.8
通讯作者：
Konstantopoulos, Spyros
中科院分区：
文献类型：
--
作者：
Konstantopoulos, Spyros
元分析方法已被广泛应用于教育、医学和社会科学。许多元分析数据是分层结构的，因为效应大小估计嵌套在研究中，反过来，研究可以嵌套在实验室或研究人员等3级单位中。因此，多水平模型是分析元分析数据的自然框架。本文讨论了Fisher计分方法在二水平和三水平Meta分析中的应用，该方法考虑了二水平和三水平的随机变异。使用提供有关学校日历类型的信息的数据展示了该模型的实用性。SAS、PROC、MIXED和HLM可用于计算固定效应和方差分量的估计。版权所有(C)2011 John Wiley&Sons，Ltd.
Meta-analytic methods have been widely applied to education, medicine, and the social sciences. Much of meta-analytic data are hierarchically structured because effect size estimates are nested within studies, and in turn, studies can be nested within level-3 units such as laboratories or investigators, and so forth. Thus, multilevel models are a natural framework for analyzing meta-analytic data. This paper discusses the application of a Fisher scoring method in two-level and three-level meta-analysis that takes into account random variation at the second and third levels. The usefulness of the model is demonstrated using data that provide information about school calendar types. SAS proc mixed and HLM can be used to compute the estimates of fixed effects and variance components. Copyright (C) 2011 John Wiley & Sons, Ltd.