Salīdzināt metodes

	Daudzgrupu mērījumu invarianču testēšana	Apstiprinošā faktoru analīze (AFA)
Nozare	Psihometrija	Psihometrija
Saime	Latent structure	Latent structure
Izcelsmes gads	1971–1993	1969
Autors	Jöreskog, K. G. (1971); Meredith, W. (1993)	Karl Gustav Jöreskog
Tips	Model comparison / hypothesis testing	Hypothesis-testing latent variable model
Pirmavots	Vandenberg, R. J. & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3(1), 4–70.	Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202.
Citi nosaukumi	measurement invariance, factorial invariance, cross-group invariance, MI testing	CFA, confirmatory FA, measurement model, restricted factor analysis
Saistītās	6	4
Kopsavilkums	Multi-group measurement invariance testing examines whether a latent construct is measured in the same way across two or more distinct groups — such as cultures, genders, or age cohorts. It is a prerequisite for meaningful group comparisons of latent means or relationships, ensuring that observed score differences reflect true differences rather than measurement artifacts.	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.