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计算多层次中介分析中特定水平的结构方程模型拟合指数

Calculating level-specific SEM fit indices for multilevel mediation analyses.

作者信息

Comulada W Scott

机构信息

Department of Psychiatry and Biobehavioral Sciences, Department of Health Policy and Management, University of California, Los Angeles, Los Angeles, CA.

出版信息

Stata J. 2021 Mar;21(1):195-205. doi: 10.1177/1536867x211000022. Epub 2021 Mar 30.

Abstract

Stata's gsem command provides the ability to fit multilevel structural equation models (sem) and related multilevel models. A motivating example is provided by multilevel mediation analyses (ma) conducted on patient data from Methadone Maintenance Treatment clinics in China. Multilevel ma conducted through the gsem command examined the mediating effects of patients' treatment progression and rapport with counselors on their treatment satisfaction. Multilevel models accounted for the clustering of patient observations within clinics. sem fit indices, such as the comparative fit index and the root mean squared error of approximation, are commonly used in the sem model selection process. Multilevel models present challenges in constructing fit indices because there are multiple levels of hierarchy to account for in establishing goodness of fit. Level-specific fit indices have been proposed in the literature but have not been incorporated into the gsem command. I created the gsemgof command to fill this role. Model results from the gsem command are used to calculate the level-specific comparative fit index and root mean squared error of approximation fit indices. I illustrate the gsemgof command through multilevel ma applied to two-level Methadone Maintenance Treatment data.

摘要

Stata的gsem命令能够拟合多层结构方程模型(SEM)及相关的多层模型。一个具有启发性的例子是对中国美沙酮维持治疗诊所的患者数据进行的多层中介分析(MA)。通过gsem命令进行的多层MA考察了患者的治疗进展以及与咨询师的融洽关系对其治疗满意度的中介作用。多层模型考虑了诊所内患者观察值的聚类情况。在SEM模型选择过程中,通常会使用一些拟合指数,比如比较拟合指数和近似误差均方根。多层模型在构建拟合指数时存在挑战,因为在确定拟合优度时需要考虑多个层次的层级结构。文献中已经提出了特定层次的拟合指数,但尚未纳入gsem命令中。我创建了gsemgof命令来发挥这一作用。gsem命令的模型结果用于计算特定层次的比较拟合指数和近似误差均方根拟合指数。我通过将多层MA应用于两级美沙酮维持治疗数据来说明gsemgof命令。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a4cd/8087284/729c565f5857/nihms-1690647-f0001.jpg

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