Suppanut Sriutaisuk, Yu Liu, Seungwon Chung, Hanjoe Kim, Fei Gu
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引用次数: 0
摘要
两阶段多重估算(MI2S)方法有望评估具有多重估算数据的序变量结构方程模型的拟合度。然而,以前的研究只考察了基于 MI2S 的残差检验统计量的性能。本研究扩展了之前的研究,检验了两种可选检验统计量的性能:均值调整检验统计量(T M)和均值与方差调整检验统计量(T MV)。我们的结果表明,在各种条件下,基于 MI2S 的 T MV 总体上优于其他测试统计量。基于 MI2S 的均方根近似误差也表现出良好的性能。本文用一组经验数据演示了 MI2S 方法,并提供了实现该方法的 Mplus 和 R 代码。
Evaluating Imputation-Based Fit Statistics in Structural Equation Modeling With Ordinal Data: The MI2S Approach
The multiple imputation two-stage (MI2S) approach holds promise for evaluating the model fit of structural equation models for ordinal variables with multiply imputed data. However, previous studies only examined the performance of MI2S-based residual-based test statistics. This study extends previous research by examining the performance of two alternative test statistics: the mean-adjusted test statistic ( T M) and the mean- and variance-adjusted test statistic ( T MV). Our results showed that the MI2S-based T MV generally outperformed other test statistics examined in a wide range of conditions. The MI2S-based root mean square error of approximation also exhibited good performance. This article demonstrates the MI2S approach with an empirical data set and provides Mplus and R code for its implementation.
期刊介绍:
ACS Applied Bio Materials is an interdisciplinary journal publishing original research covering all aspects of biomaterials and biointerfaces including and beyond the traditional biosensing, biomedical and therapeutic applications.
The journal is devoted to reports of new and original experimental and theoretical research of an applied nature that integrates knowledge in the areas of materials, engineering, physics, bioscience, and chemistry into important bio applications. The journal is specifically interested in work that addresses the relationship between structure and function and assesses the stability and degradation of materials under relevant environmental and biological conditions.