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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
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.
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页码:288 / 310
页数:23
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