השוואת שיטות
סקרו את השיטות שבחרתם זו לצד זו; שורות שבהן יש הבדל מודגשות.
| ניתוח מהימנות רב-קבוצתי× | תורת הַכְּלָלִיּוּת (G-Theory)× | |
|---|---|---|
| תחום | פסיכומטריה | פסיכומטריה |
| משפחה | Latent structure | Latent structure |
| שנת המקור≠ | 1990s–2000s | 1963–1972 |
| הוגה השיטה≠ | Classical test theory traditions; synthesized in modern practice by Vandenberg & Lance (2000) and Sijtsma (2009) | Lee J. Cronbach, Goldine Gleser, Harinder Nanda, Nageswari Rajaratnam |
| סוג≠ | Reliability estimation and comparison | Variance-components reliability model |
| מקור מכונן≠ | Vandenberg, R. J. & Lance, C. E. (2000). A review and synthesis of the measurement invariance literature: Suggestions, practices, and recommendations for organizational research. Organizational Research Methods, 3(1), 4–70. DOI ↗ | Cronbach, L. J., Gleser, G. C., Nanda, H. & Rajaratnam, N. (1972). The Dependability of Behavioral Measurements: Theory of Generalizability for Scores and Profiles. Wiley. link ↗ |
| כינויים≠ | reliability comparison across groups, group-specific reliability estimation, multi-sample reliability analysis, cross-group internal consistency | G-theory, G-study / D-study framework, variance components reliability |
| קשורות | 4 | 4 |
| תקציר≠ | Multi-group reliability analysis estimates internal consistency or stability coefficients separately within each group and then formally compares them to determine whether a scale functions with equal precision across populations. It is a foundational step in cross-group measurement research, typically carried out alongside or prior to measurement invariance testing. | Generalizability Theory is a psychometric framework that decomposes observed score variance into multiple sources — persons, items, raters, occasions, and their interactions — using analysis of variance. It replaces the single reliability coefficient of classical test theory with a family of coefficients that tell researchers how well scores generalize across different measurement conditions. |
| ScholarGateמערך נתונים ↗ |
|
|