Alternatives for Mixed-Effects Meta-Regression Models in the Reliability Generalization Approach
Alternatives for Mixed-Effects Meta-Regression Models in the Reliability Generalization Approach
复制标题
可靠性概括方法中混合效应元回归模型的替代方案
DOI：
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发表时间：
2013
期刊：
影响因子：
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通讯作者：
Fulgencio Marín
中科院分区：
文献类型：
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作者：
J. López;J. Botella;J. Sánchez;Fulgencio Marín
由于信度系数之间的异质性通常被发现在信度推广的研究，调节分析构成了元分析方法的关键步骤。在这项研究中，进行混合效应荟萃回归分析的不同程序进行了比较。具体而言，四个转换方法的可靠性系数，两个估计的残差研究间方差，和两种方法检验回归系数的显着性结合在蒙特卡洛模拟研究。在斜率估计值的偏倚和均方误差（MSE）以及斜率统计检验的I型误差和统计功效率方面比较了不同方法。模拟研究的结果并没有作为残差方差估计量的函数而变化。所有转换方法均提供负偏倚估计值，但在所有情况下偏倚和MSE均相当小。相比之下，重要的差异，发现有关统计检验，与克纳普和Hartung提出的方法显示出更好的调整，以标称的显着性水平和更高的功率比标准的方法。
Since heterogeneity between reliability coefficients is usually found in reliability generalization studies, moderator analyses constitute a crucial step for that meta-analytic approach. In this study, different procedures for conducting mixed-effects meta-regression analyses were compared. Specifically, four transformation methods for the reliability coefficients, two estimators of the residual between-studies variance, and two methods for testing regression coefficients significance were combined in a Monte Carlo simulation study. The different methods were compared in terms of bias and mean square error (MSE) of the slope estimates, and Type I error and statistical power rates for the slope statistical tests. The results of the simulation study did not vary as a function of the residual variance estimator. All transformation methods provided negatively biased estimates, but both bias and MSE were reasonably small in all cases. In contrast, important differences were found regarding statistical tests, with the method proposed by Knapp and Hartung showing a better adjustment to the nominal significance level and higher power rates than the standard method.
影响因子：
2
作者：
BERKEY, CS;HOAGLIN, DC;COLDITZ, GA
通讯作者：
COLDITZ, GA