Latent structureScale / measurement

Polytomous Exploratory Factor Analysis

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.

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  1. 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
  2. Muthén, B. (1978). Contributions to factor analysis of dichotomous variables. Psychometrika, 43(4), 551–560. DOI: 10.1007/BF02293813

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ScholarGate. (2026, June 3). Polytomous Exploratory Factor Analysis. ScholarGate. https://scholargate.app/lv/psychometrics/polytomous-exploratory-factor-analysis

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ScholarGatePolytomous EFA (Polytomous Exploratory Factor Analysis). Izgūts 2026-06-15 no https://scholargate.app/lv/psychometrics/polytomous-exploratory-factor-analysis · Datu kopa: https://doi.org/10.5281/zenodo.20539026