The Relationship Between Root Mean Square Error of Approximation and Model Misspecification in Confirmatory Factor Analysis Models

Savalei V.

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The Relationship Between Root Mean Square Error of Approximation and Model Misspecification in Confirmatory Factor Analysis Models

机译：验证性因子分析模型中近似均方根误差与模型错误指定之间的关系

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The fit index root mean square error of approximation (RMSEA) is extremely popular in structural equation modeling. However, its behavior under different scenarios remains poorly understood. The present study generates continuous curves where possible to capture the full relationship between RMSEA and various "incidental parameters," such as factor loadings and model size, for different types of misspecification. Population RMSEA is studied, removing the influence of sampling fluctuations and making the findings directly applicable to tests of close fit and not-close fit, which require the specification of a population cutoff value. Confirmatory factor analysis models are studied. The results introduce many new findings, including that RMSEA is often insensitive to multiple omitted cross-loadings and to clusters of correlated residuals, that it sometimes behaves counterintuitively as a function of model size, and that it is insensitive to the underlying number of latent factors when a model with one factor is fit.

机译：拟合指数的均方根近似误差（RMSEA）在结构方程模型中非常流行。但是，它在不同情况下的行为仍然知之甚少。本研究生成连续的曲线，以尽可能捕获RMSEA与各种“偶然参数”（例如因子负载和模型大小）之间针对不同类型的错误指定的完整关系。对人口RMSEA进行了研究，消除了样本波动的影响，并使研究结果直接适用于需要指定人口临界值的紧密拟合和非紧密拟合测试。研究验证性因素分析模型。结果引入了许多新发现，包括RMSEA通常对多个遗漏的交叉荷载和相关残差簇不敏感，有时与模型大小有关，其行为与直觉相反，并且对潜在的潜在因素数量不敏感当一个因素的模型适合时。

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《Educational and Psychological Measurement》 |2012年第6期|共23页
作者
Savalei V.;
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正文语种 eng
中图分类教育心理学;
关键词
fit indices; root mean square error of approximation (RMSEA); structural equation modeling (SEM);

机译：拟合指数;近似均方根误差（RMSEA）;结构方程模型（SEM）;

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1. The Relationship Between Root Mean Square Error of Approximation and Model Misspecification in Confirmatory Factor Analysis Models [J] . Savalei V. Educational and Psychological Measurement . 2012,第6期

机译：验证性因子分析模型中近似均方根误差与模型错误指定之间的关系
2. Erratum to: Recovery of weak factor loadings in confirmatory factor analysis under conditions of model misspecification [J] . C. Ximénez Behavior Research Methods . 2010,第1期

机译：勘误到：在模型错误指定的情况下，在验证性因子分析中恢复弱因子负载
3. Recovery of weak factor loadings in confirmatory factor analysis under conditions of model misspecification [J] . Carmen Ximenez Behavior Research Methods, Instruments & Computers . 2009,第4期

机译：在模型错误指定的情况下，在验证性因子分析中恢复弱因子负载
4. Analysis of the Mean Absolute Error (MAE) and the Root Mean Square Error (RMSE) in Assessing Rounding Model [C] . Weijie Wang, Yanmin Lu International Conference on Mechanical Engineering, Materials Science and Civil Engineering . 2018

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5. The performance of model fit measures by robust weighted least squares estimators in confirmatory factor analysis [D] . Zhao, Yu 2015

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6. A note on misspecification in general linear models with correlated errors for the analysis of crossover clinical trials [O] . Wei Wang, Ning Cong, Tian Chen, -1

机译：有关具有交叉误差的通用线性模型中错误指定的注释用于交叉临床试验的分析
7. A Comparison of Frequentist and Bayesian Approaches: The Power to Detect Model Misspecifications in Confirmatory Factor Analytic Models [O] . Emine Önen 2019

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The Relationship Between Root Mean Square Error of Approximation and Model Misspecification in Confirmatory Factor Analysis Models

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