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| Polytomisen konstruktin validiteetti× | Vahvistava faktorianalyysi (CFA)× | |
|---|---|---|
| Tieteenala | Psykometriikka | Psykometriikka |
| Menetelmäperhe | Latent structure | Latent structure |
| Syntyvuosi≠ | 1992–2000 | 1969 |
| Kehittäjä≠ | Building on Messick (1989) and IRT extensions by Masters, Muraki, and Samejima | Karl Gustav Jöreskog |
| Tyyppi≠ | Psychometric validity framework | Hypothesis-testing latent variable model |
| Alkuperäislähde≠ | Muraki, E. (1992). A generalized partial credit model: Application of an EM algorithm. Applied Psychological Measurement, 16(2), 159–176. DOI ↗ | Jöreskog, K. G. (1969). A general approach to confirmatory maximum likelihood factor analysis. Psychometrika, 34(2), 183–202. DOI ↗ |
| Rinnakkaisnimet | polytomous item construct validity, ordered-category construct validity, polytomous measurement validity, multi-category scale validity | CFA, confirmatory FA, measurement model, restricted factor analysis |
| Liittyvät≠ | 6 | 4 |
| Tiivistelmä≠ | Polytomous construct validity refers to the evaluation of whether a scale composed of ordered, multi-category items (e.g., Likert or rating-scale items) genuinely measures the intended latent construct. It extends classical validity frameworks to polytomous measurement models — such as the Graded Response Model or Generalized Partial Credit Model — ensuring that ordered response categories function as designed and that the resulting scores reflect the target construct. | 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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