Scale Freeness in Factor Analysis
Copyright policy )Scale Freeness in Factor Analysis
The notion of scale freeness does not seem to have been well understood in the factor analytic literature. It has been believed that if the loss function that is minimized to obtain estimates of the parameters in the factor model is scale invariant, then the estimates are scale free. It is shown that scale invariance of the loss function is neither a necessary nor a sufficient condition for scale freeness. A theorem that ensures scale freeness in the orthogonal factor model is given in this paper.
- University of Pittsburgh United States
- University of Massachusetts Amherst United States
- University of Massachusetts System United States
scale free estimates, generalized least squares, orthogonal factor model, identification, Factor analysis and principal components; correspondence analysis, maximum likelihood, loss function
scale free estimates, generalized least squares, orthogonal factor model, identification, Factor analysis and principal components; correspondence analysis, maximum likelihood, loss function
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