Hello All, I'm running multiple CFA models stemming from output solutions of EFA models for a thesis project. Being ordinal scaled data, polychoric matrices were used in the EFA processes. I've seen PROC CALIS METHOD=ML process the input Polychoric matrix fine, but with ULS methods, I receive the error that _TYPE_=WGT is not found, and to use the raw data set. Using the raw, Likert-scaled data set, processes fine with ULS/LSDWLS, but will these solutions take into account the ordinal properties of the data? Surely it would make a big difference. Case in point, while ML is not recommended for ordinal data, I used it to generate RMSEA estimates for both the raw data in one data step and the polychoric matrix in another. Raw Data RMSEA = 0.0550, Polychoric Data= 0.1144. Any recommendation on ensuring the ULS/DWLS methods utilize the ordinal-scaled data properly would be appreciated.
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