Thursday, October 5, 2017
Fit indices comparing indicator correlation matrices
The new menu option “Explore additional coefficients and indices”, available in WarpPLS starting in version 6.0, allows you to obtain an extended set of model fit and quality indices. The extended set of model fit and quality indices includes the classic indices already available in the previous version of this software, as well as new indices that allow investigators to assess the fit between the model-implied and empirical indicator correlation matrices. These new indices are the standardized root mean squared residual (SRMR), standardized mean absolute residual (SMAR), standardized chi-squared (SChS), standardized threshold difference count ratio (STDCR), and standardized threshold difference sum ratio (STDSR). As with the classic model fit and quality indices, the interpretation of these new indices depends on the goal of the SEM analysis. Since these indices refer to the fit between the model-implied and empirical indicator correlation matrices, they become more meaningful when the goal is to find out whether one model has a better fit with the original data than another, particularly when used in conjunction with the classic indices. When assessing the model fit with the data, several criteria are recommended. These criteria are discussed in the WarpPLS User Manual.
Related YouTube video:
Explore Indicator Correlation Matrix Fit Indices in WarpPLS
http://youtu.be/YutkhEPW-CE
Labels:
fit index,
indicator correlation matrix,
SChS,
SMAR,
SRMR,
STDCR,
STDSR,
warppls 6.0,
YouTube video
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