Testing Categorical Moderators in Mixed-Effects Meta-analysis in the Presence of Heteroscedasticity

被引:44
|
作者
Rubio-Aparicio, Maria [1 ]
Antonio Lopez-Lopez, Jose [2 ]
Viechtbauer, Wolfgang [3 ]
Marin-Martinez, Fulgencio [4 ]
Botella, Juan [5 ]
Sanchez-Meca, Julio [4 ]
机构
[1] Univ Alicante, Alicante, Spain
[2] Univ Bristol, Bristol, Avon, England
[3] Maastricht Univ, Maastricht, Netherlands
[4] Univ Murcia, Murcia, Spain
[5] Autonomous Univ Madrid, Madrid, Spain
来源
JOURNAL OF EXPERIMENTAL EDUCATION | 2020年 / 88卷 / 02期
关键词
Meta-analysis; mixed-effects model; subgroup analyses; residual between-studies variance; EFFECTS META-REGRESSION; VARIANCE ESTIMATORS; HETEROGENEITY; ANOVA;
D O I
10.1080/00220973.2018.1561404
中图分类号
G40 [教育学];
学科分类号
040101 ; 120403 ;
摘要
Mixed-effects models can be used to examine the association between a categorical moderator and the magnitude of the effect size. Two approaches are available to estimate the residual between-studies variance, -namely, separate estimation within each category of the moderator versus pooled estimation across all categories. We examine, by means of a Monte Carlo simulation study, both approaches for estimation in combination with two methods, the Wald-type and F tests, to test the statistical significance of the moderator. Results suggest that the F test using a pooled estimate of across categories is the best option in most conditions, although the F test using separate estimates of is preferable if the residual heterogeneity variances are heteroscedastic.
引用
收藏
页码:288 / 310
页数:23
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