方法对比
并排查看您选择的方法；存在差异的行会高亮显示。
| 计算机化自适应测验信度分析× | 项目反应理论 (IRT)× | |
|---|---|---|
| 领域 | 心理测量学 | 心理测量学 |
| 方法族 | Latent structure | Latent structure |
| 起源年份≠ | 1970s–1980s | 1952–1968 |
| 提出者≠ | David J. Weiss and IRT psychometricians | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| 类型≠ | Reliability estimation under adaptive testing | Probabilistic measurement model |
| 开创性文献≠ | Weiss, D. J. (1984). Application of computerized adaptive testing to educational problems. Journal of Educational Measurement, 21(4), 361–375. DOI ↗ | Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗ |
| 别名 | CAT reliability, adaptive test reliability, IRT-based reliability estimation, marginal reliability in CAT | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| 相关≠ | 4 | 5 |
| 摘要≠ | CAT reliability analysis quantifies measurement precision in computerized adaptive tests where each examinee receives a unique, individually tailored subset of items. Rather than a single classical coefficient, it uses item response theory to express precision as conditional standard error of measurement at each ability level, and marginal reliability as a global summary across the ability distribution. | Item response theory models the probability that a respondent answers an item correctly (or endorses it) as a function of the respondent's latent trait level and the item's own statistical properties — difficulty, discrimination, and guessing. Unlike classical test theory, IRT places persons and items on the same scale, yielding measurement that is sample-independent for items and test-independent for persons. |
| ScholarGate数据集 ↗ |
|
|