Σύγκριση μεθόδων
Εξετάστε τις επιλεγμένες μεθόδους δίπλα-δίπλα· οι γραμμές που διαφέρουν επισημαίνονται.
| Δοκιμή αναλλοιότητας μετρήσεων σε διατακτική κλίμακα× | Επαληθευτική Παραγοντική Ανάλυση (Confirmatory Factor Analysis - CFA)× | |
|---|---|---|
| Πεδίο | Ψυχομετρία | Ψυχομετρία |
| Οικογένεια | Latent structure | Latent structure |
| Έτος προέλευσης≠ | 1984–2011 | 1969 |
| Δημιουργός≠ | Roger Millsap; Bengt Muthén | Karl Gustav Jöreskog |
| Τύπος≠ | Multi-group model comparison | Hypothesis-testing latent variable model |
| Θεμελιώδης πηγή≠ | Millsap, R. E. (2011). Statistical Approaches to Measurement Invariance. Routledge. ISBN: 978-1848728936 | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| Εναλλακτικές ονομασίες | ordinal MI, measurement invariance for ordinal data, ordinal CFA invariance, categorical measurement invariance | CFA, confirmatory FA, measurement model, restricted factor analysis |
| Συναφείς≠ | 6 | 4 |
| Σύνοψη≠ | 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. | 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. |
| ScholarGateΣύνολο δεδομένων ↗ |
|
|