Linganisha mbinu

	Upimishaji wa uhakikisho wa kipimo cha ordinal	Uchanganuzi wa Uthibiti wa Vipengele vya Vikundi Nyingi (MG-CFA)
Nyanja	Saikometriki	Saikometriki
Familia	Latent structure	Latent structure
Mwaka wa asili	1984–2011	1971
Mwanzilishi	Roger Millsap; Bengt Muthén	Karl Jöreskog
Aina	Multi-group model comparison	Measurement model / invariance test
Chanzo asilia	Millsap, R. E. (2011). Statistical Approaches to Measurement Invariance. Routledge. ISBN: 978-1848728936	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.
Majina mbadala	ordinal MI, measurement invariance for ordinal data, ordinal CFA invariance, categorical measurement invariance	MG-CFA, multi-group CFA, measurement invariance testing, multi-sample CFA
Zinazohusiana	6	6
Muhtasari	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.	Multi-group confirmatory factor analysis tests whether a measurement model holds equivalently across two or more groups — such as cultures, genders, or time points. By imposing increasingly stringent equality constraints and comparing model fit, it determines whether comparisons of latent mean scores are justified.