Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Uchanganuzi wa Kipengele cha Kuthibitisha wa Polytomous× | Uchanganuzi wa Kimfumo wa Uhakiki (CFA)× | |
|---|---|---|
| Nyanja | Saikometriki | Saikometriki |
| Familia | Latent structure | Latent structure |
| Mwaka wa asili≠ | 1984 | 1969 |
| Mwanzilishi≠ | Bengt Muthen | Karl Gustav Jöreskog |
| Aina≠ | Latent variable / confirmatory measurement model | Hypothesis-testing latent variable model |
| Chanzo asilia≠ | Flora, D. B. & Curran, P. J. (2004). An empirical evaluation of alternative methods of estimation for confirmatory factor analysis with ordinal data. Psychological Methods, 9(4), 466–491. DOI ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| Majina mbadala | CFA for ordered categories, ordinal CFA, categorical CFA, WLSMV-CFA | CFA, confirmatory FA, measurement model, restricted factor analysis |
| Zinazohusiana≠ | 5 | 4 |
| Muhtasari≠ | Polytomous confirmatory factor analysis (CFA) tests a pre-specified factor structure when items have three or more ordered response categories (e.g., Likert scales). By working with polychoric correlations and robust estimators such as WLSMV, it avoids the distortions that arise when ordered categorical 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. |
| ScholarGateSeti ya data ↗ |
|
|