Linganisha mbinu

	Uthabiti wa Upimaji wa Polytomous	Uchanganuzi wa Kimfumo wa Uhakiki (CFA)
Nyanja	Saikometriki	Saikometriki
Familia	Latent structure	Latent structure
Mwaka wa asili	2000–2004	1969
Mwanzilishi	Roger E. Millsap, Robert J. Vandenberg	Karl Gustav Jöreskog
Aina	Multi-group confirmatory test	Hypothesis-testing latent variable model
Chanzo asilia	Millsap, R. E. & Kwok, O.-M. (2004). Evaluating the impact of partial factor loading and intercept invariance on selection utility. Psychological Methods, 9(2), 200–215.	Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202.
Majina mbadala	PMI, ordinal measurement invariance, polytomous factorial invariance, polytomous multi-group measurement invariance	CFA, confirmatory FA, measurement model, restricted factor analysis
Zinazohusiana	5	4
Muhtasari	Polytomous measurement invariance testing evaluates whether a scale with ordered categorical (polytomous) response options — such as Likert-type items — measures the same latent construct in the same way across two or more groups. It extends classical multi-group CFA invariance testing to properly account for the ordinal nature of item responses, ensuring that group comparisons of latent means or factor structures are substantively valid.	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.