Polytomous EFA
Polytomous exploratory factor analysis extends standard EFA to ordered categorical (Likert-type) response data by replacing the Pearson correlation matrix with a polychoric correlation matrix. It recovers the latent continuous variable that each polytomous item is assumed to reflect, yielding more accurate factor loadings and better-defined factor structures than treating ordinal scores as if they were continuous.
Source record
Citations copied verbatim from the method’s source record. No claim-level verification is inferred from them.
- Flora, D. B., & Curran, P. J. (2004). An empirical evaluation of alternative methods of estimation for confirmatory factor analysis with ordinal data. Psychological Methods, 9(4), 466–491. · DOI 10.1037/1082-989X.9.4.466
- Muthén, B. (1978). Contributions to factor analysis of dichotomous variables. Psychometrika, 43(4), 551–560. · DOI 10.1007/BF02293813
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