Bandingkan kaedah
Semak kaedah pilihan anda secara bersebelahan; baris yang berbeza akan diserlahkan.
| Pengujian Invarians Pengukuran Ordinal× | Analisis Faktor Pengesahan Ordinal× | |
|---|---|---|
| Bidang | Psikometrik | Psikometrik |
| Keluarga | Latent structure | Latent structure |
| Tahun asal≠ | 1984–2011 | 1984 |
| Pengasas≠ | Roger Millsap; Bengt Muthén | Bengt O. Muthén |
| Jenis≠ | Multi-group model comparison | Latent variable / structural |
| Sumber perintis≠ | Millsap, R. E. (2011). Statistical Approaches to Measurement Invariance. Routledge. ISBN: 978-1848728936 | 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 ↗ |
| Alias | ordinal MI, measurement invariance for ordinal data, ordinal CFA invariance, categorical measurement invariance | CFA for ordinal data, polychoric CFA, WLSMV CFA, categorical CFA |
| Berkaitan≠ | 6 | 5 |
| Ringkasan≠ | 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. | 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. |
| ScholarGateSet data ↗ |
|
|