השוואת שיטות
סקרו את השיטות שבחרתם זו לצד זו; שורות שבהן יש הבדל מודגשות.
| ניתוח גורמים מאשר אורך× | ניתוח גורמים מאשר רב-רמתי (MCFA)× | |
|---|---|---|
| תחום | פסיכומטריה | פסיכומטריה |
| משפחה | Latent structure | Latent structure |
| שנת המקור≠ | 1970s–1990s | 1994 |
| הוגה השיטה≠ | Karl Jöreskog (CFA framework); longitudinal extension by Wheaton, Muthén, and Alwin in the 1970s–1990s | Bengt O. Muthen |
| סוג≠ | Longitudinal latent variable / measurement model | Latent variable model / measurement model |
| מקור מכונן≠ | Widaman, K. F. & Reise, S. P. (1997). Exploring the measurement invariance of psychological instruments: Applications in the substance use domain. In K. J. Bryant, M. Windle & S. G. West (Eds.), The science of prevention: Methodological advances from alcohol and substance abuse research (pp. 281–324). American Psychological Association. link ↗ | Muthen, B. O. (1994). Multilevel covariance structure analysis. Sociological Methods & Research, 22(3), 376–398. DOI ↗ |
| כינויים | longitudinal CFA, repeated-measures CFA, longitudinal measurement model, panel CFA | MCFA, multilevel measurement model, two-level CFA, hierarchical CFA |
| קשורות | 6 | 6 |
| תקציר≠ | Longitudinal confirmatory factor analysis (longitudinal CFA) applies a theoretically specified measurement model to data collected at two or more time points. Its primary purpose is to verify that a scale measures the same latent construct in the same way over time — a prerequisite for drawing valid conclusions about change from repeated-measures data. | Multilevel confirmatory factor analysis tests a pre-specified factor structure while simultaneously accounting for the non-independence of observations caused by clustered data. It decomposes item variance into within-group and between-group components, fitting a separate measurement model at each level, making it the standard tool for validating psychometric scales administered within natural groups such as classrooms, clinics, or organisations. |
| ScholarGateמערך נתונים ↗ |
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