We discuss the effects of missing data on X-based goodness-of-fit indices in Structural Equation Modeling (SEM), specifically on the Root Mean Squared Error of Approximation (RMSEA). We use simulations to show that naive implementations of the RMSEA have a downward bias in the p...
The root mean square error of approximation (RMSEA) is a popular fit index in structural equation modeling (SEM). Typically, RMSEA is computed using the no... PE Brosseau-Liard,V Savalei,L Li - 《Multivariate Behavioral Research》 被引量: 32发表: 2012年 Structural Equation Modeling of Laten...
In this study, the minimum sample size required for formal research was calculated [22]: 223 participants were required to achieve a statistical power of 95% by assuming an intraclass correlation coefficient (ICC) of 0.90 and a Type I error probability α of 0.05. A total of 10,951 valid ...
Therefore, the Satorra-Bentler-scaled chi-square statistic was applied as a goodness of fit statistics40,47,48. Furthermore, the root mean square error of approximation (RMSEA) (≤ 0.05 good fit, ≤ 0.10 acceptable) and the standardized root mean square residual (SRMS) (≤ 0.05 ...
ratios,the resolution success rate of theproposed algorithm is higher than that of the traditional Caponalgorithm.Moreover,the root-mean-square error of the proposed algorithm issignificantly better than the classic Capon algorithm.
To evaluate the measurement invariance, the changes of several indices were presented, consisting of changes in chi-square statistics (Δχ2), comparative fit index (ΔCFI), and root mean square error of approximation (ΔRMSEA). ΔCFI < 0.01 and ΔRMSEA < 0.015 indicated measurement ...
Theroot mean squareserror of prediction (RMSEP) was calculated based on the AutoFom III predicted values and the reference values. Prediction errors were evaluated by determining theroot mean squareserrors of calibration (RMSEC),root mean squareserror of cross validation (RMSECV), and RMSEP. ...
The Standardized Root Mean Square Residual (SRMR) is also reported, as well as the Root Mean Square Error of Approximation (RMSEA), Bentler’s Comparative Fit Index (CFI), and the Tucker-Lewis Index (TLI). Hu and Bentler [45] suggest that values below 0.08 for SRMR and 0.06 for RMSEA ...
The model fit indices include comparative fit index (CFI; Bentler, 1990) and Tucker-Lewis index (TLI; Tucker & Lewis, 1973) with acceptable fit ≥ .90 and good fit ≥ .95, root mean square error of approximation (RMSEA; Steiger & Lind, 1980) with acceptable fit < .06 and standardized...
The RMS (square root of mean square error, MSE) is the most important because it quantifies estimation accuracy. Bias requires only the first-order moments, whereas the deviation variance and RMS require also the second-order moments. Historically, analytic study has mainly focused on the first...