Linganisha mbinu
Pitia mbinu ulizochagua bega kwa bega; safu zinazotofautiana zinaangaziwa.
| Uimla wa kuegemeza wa vipimo vingi (Multilevel Test-Retest Reliability)× | Uchanganuzi wa Kimfumo wa Uhakiki (CFA)× | |
|---|---|---|
| Nyanja | Saikometriki | Saikometriki |
| Familia | Latent structure | Latent structure |
| Mwaka wa asili≠ | 1979 (ICC foundation); multilevel extension: 1990s–2000s | 1969 |
| Mwanzilishi≠ | Shrout & Fleiss (ICC foundation); multilevel extension by Goldstein, Snijders, and others | Karl Gustav Jöreskog |
| Aina≠ | Reliability estimation under hierarchical data | Hypothesis-testing latent variable model |
| Chanzo asilia≠ | Shrout, P. E. & Fleiss, J. L. (1979). Intraclass correlations: Uses in assessing rater reliability. Psychological Bulletin, 86(2), 420–428. DOI ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| Majina mbadala | hierarchical test-retest reliability, multilevel ICC reliability, nested test-retest reliability, ML-TRT reliability | CFA, confirmatory FA, measurement model, restricted factor analysis |
| Zinazohusiana≠ | 5 | 4 |
| Muhtasari≠ | Multilevel test-retest reliability estimates how consistently a measurement instrument produces the same scores across repeated administrations when observations are nested within higher-level units — such as patients within clinics or students within classrooms. It partitions total score variance across levels using intraclass correlation coefficients derived from multilevel models. | 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. |
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