用模型隐含工具变量估计和检验随机截距多水平结构方程模型。

IF 2.5 2区 心理学 Q2 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS Structural Equation Modeling: A Multidisciplinary Journal Pub Date : 2022-01-01 DOI:10.1080/10705511.2022.2028261
Michael L Giordano, Kenneth A Bollen, Shaobo Jin
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引用次数: 0

摘要

针对随机截距多层结构方程模型,提出了一种新的有限信息估计方法。它基于模型隐含工具变量两阶段最小二乘(MIIV-2SLS)估计器,该估计器已被证明是sem中最大似然(ML)的极好替代或补充(Bollen, 1996)。我们还开发了一个多水平过度识别检验统计量,适用于水平内或水平之间的方程。我们的蒙特卡罗模拟分析表明,miv - 2sls在级别内或级别之间的错误规范方面比ML更具鲁棒性,在少于100个集群的情况下表现良好,并且表明我们对方程的多级过度识别测试在模型的两个级别上都表现良好。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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Estimating and Testing Random Intercept Multilevel Structural Equation Models with Model Implied Instrumental Variables.

This study develops a new limited information estimator for random intercept Multilevel Structural Equation Models (MSEM). It is based on the Model Implied Instrumental Variable Two-Stage Least Squares (MIIV-2SLS) estimator, which has been shown to be an excellent alternative or supplement to maximum likelihood (ML) in SEMs (Bollen, 1996). We also develop a multilevel overidentification test statistic that applies to equations at the within or between levels. Our Monte Carlo simulation analysis suggests that MIIV-2SLS is more robust than ML to misspecification at within or between levels, performs well given fewer that 100 clusters, and shows that our multilevel overidentification test for equations performs well at both levels of the model.

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来源期刊
CiteScore
8.70
自引率
11.70%
发文量
71
审稿时长
>12 weeks
期刊介绍: Structural Equation Modeling: A Multidisciplinary Journal publishes refereed scholarly work from all academic disciplines interested in structural equation modeling. These disciplines include, but are not limited to, psychology, medicine, sociology, education, political science, economics, management, and business/marketing. Theoretical articles address new developments; applied articles deal with innovative structural equation modeling applications; the Teacher’s Corner provides instructional modules on aspects of structural equation modeling; book and software reviews examine new modeling information and techniques; and advertising alerts readers to new products. Comments on technical or substantive issues addressed in articles or reviews published in the journal are encouraged; comments are reviewed, and authors of the original works are invited to respond.
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