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| 稳健拉斯模型× | 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≠ | 1982 | 1952–1968 |
| 提出者≠ | Mislevy & Bock (robust ability estimation); broader robust IRT formalized through 1980s–2000s | Frederic M. Lord (and Allan Birnbaum for the 2PL/3PL models) |
| 类型≠ | Robust item calibration model | Probabilistic measurement model |
| 开创性文献≠ | Strobl, C., Wickelmaier, F., & Zeileis, A. (2011). Accounting for individual differences in Bradley-Terry models by means of recursive partitioning. Journal of Educational and Behavioral Statistics, 36(2), 135–153. DOI ↗ | Lord, F. M. & Novick, M. R. (1968). Statistical Theories of Mental Test Scores. Addison-Wesley. link ↗ |
| 别名 | robust IRT Rasch, robust dichotomous Rasch, outlier-resistant Rasch model, robust item calibration | IRT, latent trait theory, item characteristic curve theory, modern test theory |
| 相关 | 5 | 5 |
| 摘要≠ | The robust Rasch model applies the standard one-parameter logistic Rasch framework with estimation procedures designed to limit the influence of outlying item responses, aberrant respondents, or mild model violations, producing stable item and person parameter estimates that are less sensitive to data contamination than ordinary maximum likelihood or conditional maximum likelihood Rasch estimation. | 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. |
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