Salīdzināt metodes

	Ordinālās mērīšanas invariances testēšana	Ordinal Confirmatory Factor Analysis
Nozare	Psihometrija	Psihometrija
Saime	Latent structure	Latent structure
Izcelsmes gads	1984–2011	1984
Autors	Roger Millsap; Bengt Muthén	Bengt O. Muthén
Tips	Multi-group model comparison	Latent variable / structural
Pirmavots	Millsap, R. E. (2011). Statistical Approaches to Measurement Invariance. Routledge. ISBN: 978-1848728936	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.
Citi nosaukumi	ordinal MI, measurement invariance for ordinal data, ordinal CFA invariance, categorical measurement invariance	CFA for ordinal data, polychoric CFA, WLSMV CFA, categorical CFA
Saistītās	6	5
Kopsavilkums	Ordinal measurement invariance testing evaluates whether a multi-group confirmatory factor model holds equivalent measurement properties across groups when scale items are ordinal — such as Likert-type response scales. It uses polychoric correlations and categorical estimators (WLSMV/DWLS) rather than Pearson-based methods, correcting the systematic bias that arises when ordinal data are treated as continuous.	Ordinal confirmatory factor analysis (Ordinal CFA) tests a pre-specified factor structure when the observed indicators are ordinal — typically Likert-type survey items. By using polychoric correlations and robust estimators such as WLSMV, it avoids the bias that arises from treating categorical responses as continuous.