Nonnormal and categorical data in structural equation modeling

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Unlocking the black box: exploring the link between high-performance work systems and performance. (2011, background): “RWLS does not require strict distributional assumptions and provides robust estimates in small sample settings (Finney & DiStefano, 2006).”
The Self-Expressive Edge of Occupational Sex Segregation1 (2013, methodology): “ÞAs such, there is no assumed distortion in the SEM fit indices from the use of noncontinuous variables ðFinney and DiStefano 2006Þ. 26Latentmeasures aremeant to represent overarching concepts, the components ofwhich are captured by the manifest variables predicted by the latent measure ðByrne…”
A Comparison of Diagonal Weighted Least Squares Robust Estimation Techniques for Ordinal Data (2014, background): “Robust estimation techniques could prove useful when data are coarsely categorized or follow nonnormal distributions (e.g., Finney & DiStefano, 2006).”