Constructing a Robust Score Scale from IRT Scores with Informed Boundaries.
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| Title: | Constructing a Robust Score Scale from IRT Scores with Informed Boundaries. |
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| Authors: | Choe, Edison M. (AUTHOR) edison.choe@renaissance.com, Han, Kyung T. (AUTHOR) khan@gmac.com |
| Source: | Journal of Educational Measurement. Mar2022, Vol. 59 Issue 1, p4-21. 18p. |
| Subject Terms: | *Cognitive ability, *Item response theory |
| Abstract: | In operational testing, item response theory (IRT) models for dichotomous responses are popular for measuring a single latent construct θ$\theta$, such as cognitive ability in a content domain. Estimates of θ$\theta$, also called IRT scores or θ̂$\hat{\theta }$, can be computed using estimators based on the likelihood function, such as maximum likelihood (ML), weighted likelihood (WL), maximum a posteriori (MAP), and expected a posteriori (EAP). Although the parameter space of θ$\theta$ is theoretically unrestricted, the range of finite θ̂$\hat{\theta }$ is constrained by the estimator and test form properties, which is important to consider but often overlooked when developing a score scale for reporting purposes. Irrespective of the estimator or test forms at hand, a common practice is to fix arbitrary points symmetric about zero (e.g., −4 and 4) as anchors for deriving a score transformation, possibly resulting in unintended gaps or truncations at the extremes. Therefore, a systematic framework is proposed for using IRT scores to construct a robust score scale with informed boundaries that are logical and consistent across test forms. [ABSTRACT FROM AUTHOR] |
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| Database: | Education Research Complete |
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| Abstract: | In operational testing, item response theory (IRT) models for dichotomous responses are popular for measuring a single latent construct θ$\theta$, such as cognitive ability in a content domain. Estimates of θ$\theta$, also called IRT scores or θ̂$\hat{\theta }$, can be computed using estimators based on the likelihood function, such as maximum likelihood (ML), weighted likelihood (WL), maximum a posteriori (MAP), and expected a posteriori (EAP). Although the parameter space of θ$\theta$ is theoretically unrestricted, the range of finite θ̂$\hat{\theta }$ is constrained by the estimator and test form properties, which is important to consider but often overlooked when developing a score scale for reporting purposes. Irrespective of the estimator or test forms at hand, a common practice is to fix arbitrary points symmetric about zero (e.g., −4 and 4) as anchors for deriving a score transformation, possibly resulting in unintended gaps or truncations at the extremes. Therefore, a systematic framework is proposed for using IRT scores to construct a robust score scale with informed boundaries that are logical and consistent across test forms. [ABSTRACT FROM AUTHOR] |
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| ISSN: | 00220655 |
| DOI: | 10.1111/jedm.12307 |
