

EFA with categorical indicators 

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Hello. I was running an EFA using oblique rotation (I believe Oblimin rotation is the default) for three ordinal, Likertscale items, and 2 questions came up when I examined the output, which had 0 degrees of freedom since the model is just identified. 1.) I changed the default estimation method and used ML estimation because I wanted my results to relate to the overall population and not just to my data. Is OK to use ML estimation in Mplus when running an EFA with 3 ordinal indicators? 2.) Since factor loadings are often interpreted as regression coefficients, could I interpret both my unrotated and rotated factor loadings as I would a logisitic or even an ordinal probit model (e.g., regressing the observed ordinal variable on the latent factor)? Thanks. 


With three factor indicators, only one factor can be extracted. This means that there can be no rotation. I'm not sure what you mean by "relate to the overall population and not just my data". All estimators do this. It is okay to use ML with ordinal indicators. The factor loadings with ML and categorical outcomes are logistic regression coefficients unless LINK=PROBIT is used. Then they are probit regression coefficients. 

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