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Observed-Score Equating With a Heterogeneous Target Population.

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Title: Observed-Score Equating With a Heterogeneous Target Population.
Authors: Duong, MinhQ. (AUTHOR), von Davier, AlinaA. (AUTHOR)
Source: International Journal of Testing. 2012, Vol. 12 Issue 3, p224-251. 28p.
Subjects: Educational tests & measurements, Item response theory, Statistical sampling, Distribution (Probability theory), Probability theory
Abstract: Test equating is a statistical procedure for adjusting for test form differences in difficulty in a standardized assessment. Equating results are supposed to hold for a specified target population (Kolen & Brennan, 2004; von Davier, Holland, & Thayer, 2004) and to be (relatively) independent of the subpopulations from the target population (see Dorans & Holland, 2000; Zumbo, 2007). This study discusses the challenges in defining a target population for test equating and in validating the inferences that can be made for the equated scores when the test takers cluster in distinctive ability groups. This discussion takes place in the context of measurement validity (Zumbo, 2007) and optimal sampling design (Berger, 1997). This article discusses an alternative observed-score equating (OSE) approach that takes the advantage of the OSE framework described in von Davier (2011). The flexibility of the OSE framework and the availability of the standard error of equating difference, which is the standard error of the difference between two equating functions obtained from using two different methods, allow practitioners to compare statistically the equating results from different weighting schemes for distinctive subgroups of the target population. Simulated and real data were used in this study. Item response theory OSE with multigroup calibration, followed by computing the distributions with appropriate sampling weights, was used as the equating criterion. [ABSTRACT FROM PUBLISHER]
Copyright of International Journal of Testing is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Observed-Score Equating With a Heterogeneous Target Population.
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  Data: <searchLink fieldCode="AR" term="%22Duong%2C+MinhQ%2E%22">Duong, MinhQ.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22von+Davier%2C+AlinaA%2E%22">von Davier, AlinaA.</searchLink> (AUTHOR)
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  Data: Test equating is a statistical procedure for adjusting for test form differences in difficulty in a standardized assessment. Equating results are supposed to hold for a specified target population (Kolen & Brennan, 2004; von Davier, Holland, & Thayer, 2004) and to be (relatively) independent of the subpopulations from the target population (see Dorans & Holland, 2000; Zumbo, 2007). This study discusses the challenges in defining a target population for test equating and in validating the inferences that can be made for the equated scores when the test takers cluster in distinctive ability groups. This discussion takes place in the context of measurement validity (Zumbo, 2007) and optimal sampling design (Berger, 1997). This article discusses an alternative observed-score equating (OSE) approach that takes the advantage of the OSE framework described in von Davier (2011). The flexibility of the OSE framework and the availability of the standard error of equating difference, which is the standard error of the difference between two equating functions obtained from using two different methods, allow practitioners to compare statistically the equating results from different weighting schemes for distinctive subgroups of the target population. Simulated and real data were used in this study. Item response theory OSE with multigroup calibration, followed by computing the distributions with appropriate sampling weights, was used as the equating criterion. [ABSTRACT FROM PUBLISHER]
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  Data: <i>Copyright of International Journal of Testing is the property of Taylor & Francis Ltd and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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        Text: English
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        Type: general
      – SubjectFull: Item response theory
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      – SubjectFull: Statistical sampling
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