Bandingkan metode
Tinjau metode pilihan Anda berdampingan; baris yang berbeda akan disorot.
| Analisis Faktor Konfirmatori Ordinal× | Teori Respons Item (TRI)× | |
|---|---|---|
| Bidang | Psikometri | Psikometri |
| Keluarga | Latent structure | Latent structure |
| Tahun asal≠ | 1984 | 1952–1968 |
| Pencetus≠ | Bengt O. Muthén | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| Tipe≠ | Latent variable / structural | Probabilistic measurement model |
| Sumber perintis≠ | 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 ↗ | Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗ |
| Alias | CFA for ordinal data, polychoric CFA, WLSMV CFA, categorical CFA | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| Terkait | 5 | 5 |
| Ringkasan≠ | Ordinal confirmatory factor analysis (Ordinal CFA) tests a pre-specified factor structure when the observed indicators are ordinal — typically Likert-type survey items. By using polychoric correlations and robust estimators such as WLSMV, it avoids the bias that arises from treating categorical responses as continuous. | Item response theory models the probability that a respondent answers an item correctly (or endorses it) as a function of the respondent's latent trait level and the item's own statistical properties — difficulty, discrimination, and guessing. Unlike classical test theory, IRT places persons and items on the same scale, yielding measurement that is sample-independent for items and test-independent for persons. |
| ScholarGateSet data ↗ |
|
|