结构方程模型中模型不拟合的影响大小:标准化残差协方差和残差相关性

IF 2 3区 心理学 Q2 PSYCHOLOGY, MATHEMATICAL
Albert Maydeu-Olivares, Dexin Shi
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引用次数: 31

摘要

残差相关和协方差提供了协方差结构模型失配的效应大小。在一项模拟研究中,我们发现即使在小样本(N = 100)中,无论模型大小、模型错配程度和数据分布如何,标准化残差协方差的准确置信区间(ci)也能得到。标准化的残差协方差也提供了在拟合不良的模型中失配的来源的信息。从这个角度来看,它们可以被视为修改索引的替代方案。我们比较了标准化残差协方差和修正指数的经验I型误差和功率率,发现这两种方法在所调查的模拟条件下提供了几乎相同的率。残差相关和标准化残差协方差提供了非常相似的结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Effect Sizes of Model Misfit in Structural Equation Models: Standardized Residual Covariances and Residual Correlations
Residual correlations and covariances provide effect sizes of the misfit of covariance structure models. In a simulation study, we found that accurate confidence intervals (CIs) for standardized residual covariances are obtained even in small samples (N = 100), regardless of model size, degree of model misspecification, and data distribution. Standardized residual covariances also provide information about the source of misfit in poorly fitting models. From this viewpoint, they may be considered an alternative to modification indices. We compared the empirical Type I errors and power rates of standardized residual covariances and modification indices and found that both procedures provide nearly identical rates across the simulation conditions investigated. Residual correlations and standardized residual covariances provide very similar results.
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来源期刊
CiteScore
2.70
自引率
6.50%
发文量
16
审稿时长
36 weeks
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