Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Uchanganuzi wa Kiwango cha Dondoo wa Vipengele× | Uchanganuzi wa Vipengele vya Uchunguzi (EFA)× | |
|---|---|---|
| Nyanja≠ | Saikometriki | Takwimu |
| Familia | Latent structure | Latent structure |
| Mwaka wa asili≠ | 1978–1984 | — |
| Mwanzilishi≠ | Bengt Muthén | — |
| Aina | Latent variable / dimension reduction | Latent variable / dimension reduction |
| 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 ↗ | Fabrigar, L. R., Wegener, D. T., MacCallum, R. C. & Strahan, E. J. (1999). Evaluating the use of exploratory factor analysis in psychological research. Psychological Methods, 4(3), 272–299. DOI ↗ |
| Majina mbadala≠ | ordinal factor analysis, polychoric EFA, categorical EFA, EFA for ordinal data | common factor analysis, açımlayıcı faktör analizi, factor analysis |
| Zinazohusiana≠ | 5 | 4 |
| Muhtasari≠ | Ordinal exploratory factor analysis discovers latent factors underlying a set of ordinal items — typically Likert scales — by computing polychoric correlations among the items and then applying a weighted least squares estimator. It avoids the distortions that arise when continuous EFA methods are naively applied to ordered categorical responses. | Exploratory factor analysis reduces a large set of observed variables into a smaller number of latent common factors. It is widely used in scale development and psychometrics to uncover the dimensional structure that underlies a set of correlated items, without specifying that structure in advance. |
| ScholarGateSeti ya data ↗ |
|
|