Salīdzināt metodes

	Ordinālās mērīšanas invariances testēšana	Apstiprinošā faktoru analīze (AFA)
Nozare	Psihometrija	Psihometrija
Saime	Latent structure	Latent structure
Izcelsmes gads	1984–2011	1969
Autors	Roger Millsap; Bengt Muthén	Karl Gustav Jöreskog
Tips	Multi-group model comparison	Hypothesis-testing latent variable model
Pirmavots	Millsap, R. E. (2011). Statistical Approaches to Measurement Invariance. Routledge. ISBN: 978-1848728936	Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202.
Citi nosaukumi	ordinal MI, measurement invariance for ordinal data, ordinal CFA invariance, categorical measurement invariance	CFA, confirmatory FA, measurement model, restricted factor analysis
Saistītās	6	4
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.	Confirmatory factor analysis tests a researcher-specified factor structure against observed data. Unlike exploratory approaches, the researcher decides in advance which indicators load on which latent factor, and the model is evaluated by how closely the implied covariance matrix reproduces the sample covariance matrix. CFA is central to scale validation, construct validity assessment, and measurement invariance testing.