השוואת שיטות
סקרו את השיטות שבחרתם זו לצד זו; שורות שבהן יש הבדל מודגשות.
| ניתוח מחלקות סמויות (LCA)× | ניתוח גורמים מאשר (CFA)× | |
|---|---|---|
| תחום≠ | סטטיסטיקה | פסיכומטריה |
| משפחה | Latent structure | Latent structure |
| שנת המקור≠ | 1950s–1968 | 1969 |
| הוגה השיטה≠ | Paul F. Lazarsfeld | Karl Gustav Jöreskog |
| סוג≠ | Latent variable / person-centered classification | Hypothesis-testing latent variable model |
| מקור מכונן≠ | Goodman, L. A. (1974). Exploratory latent structure analysis using both identifiable and unidentifiable models. Biometrika, 61(2), 215–231. DOI ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| כינויים | LCA, latent class model, latent categorical analysis, finite mixture of multinomials | CFA, confirmatory FA, measurement model, restricted factor analysis |
| קשורות≠ | 6 | 4 |
| תקציר≠ | Latent class analysis identifies unobserved subgroups — latent classes — within a population by finding patterns of responses across a set of categorical observed indicators. It is the categorical-variable counterpart of cluster analysis, but grounded in an explicit probabilistic model, and is widely used in social, health, and behavioral sciences to discover typologies in survey or diagnostic data. | 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. |
| ScholarGateמערך נתונים ↗ |
|
|