Linganisha mbinu

	Uchanganuzi Imara wa Kipengele cha Uthibitisho	Uchanganuzi wa Kimfumo wa Uhakiki (CFA)
Nyanja	Takwimu	Saikometriki
Familia	Latent structure	Latent structure
Mwaka wa asili	1984–1994	1969
Mwanzilishi	Satorra & Bentler (robust SE/chi-square corrections); Browne (ADF estimator)	Karl Gustav Jöreskog
Aina	Confirmatory latent variable model with robust estimation	Hypothesis-testing latent variable model
Chanzo asilia	Satorra, A. & Bentler, P. M. (1994). Corrections to test statistics and standard errors in covariance structure analysis. In A. von Eye & C. C. Clogg (Eds.), Latent variables analysis: Applications for developmental research (pp. 399–419). Sage.	Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202.
Majina mbadala	Robust CFA, CFA with robust standard errors, Satorra-Bentler CFA, non-normal CFA	CFA, confirmatory FA, measurement model, restricted factor analysis
Zinazohusiana	6	4
Muhtasari	Robust confirmatory factor analysis fits a pre-specified factor structure to observed data while correcting standard errors and goodness-of-fit statistics for violations of multivariate normality. It is the preferred variant of CFA whenever Likert-type, skewed, or kurtotic indicators make the classical normal-theory estimator unreliable.	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.