Stabilizing Conditional Standard Errors of Measurement in Scale Score Transformations.
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| Title: | Stabilizing Conditional Standard Errors of Measurement in Scale Score Transformations. |
|---|---|
| Authors: | Moses, Tim1, Kim, YoungKoung1 |
| Source: | Journal of Educational Measurement. Summer2017, Vol. 54 Issue 2, p184-199. 16p. |
| Subject Terms: | *Item response theory, Measurement errors, Analysis of variance, Arcsine function, Distribution (Probability theory) |
| Abstract: | The focus of this article is on scale score transformations that can be used to stabilize conditional standard errors of measurement (CSEMs). Three transformations for stabilizing the estimated CSEMs are reviewed, including the traditional arcsine transformation, a recently developed general variance stabilization transformation, and a new method proposed in this article involving cubic transformations. Two examples are provided and the three scale score transformations are compared in terms of how well they stabilize CSEMs estimated from compound binomial and item response theory (IRT) models. Advantages of the cubic transformation are demonstrated with respect to CSEM stabilization and other scaling criteria (e.g., scale score distributions that are more symmetric). [ABSTRACT FROM AUTHOR] |
| Copyright of Journal of Educational Measurement is the property of Wiley-Blackwell 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: | Education Research Complete |
| FullText | Links: – Type: pdflink Text: Availability: 0 |
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| Header | DbId: ehh DbLabel: Education Research Complete An: 123349884 AccessLevel: 6 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: Stabilizing Conditional Standard Errors of Measurement in Scale Score Transformations. – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Moses%2C+Tim%22">Moses, Tim</searchLink><relatesTo>1</relatesTo><br /><searchLink fieldCode="AR" term="%22Kim%2C+YoungKoung%22">Kim, YoungKoung</searchLink><relatesTo>1</relatesTo> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="JN" term="%22Journal+of+Educational+Measurement%22">Journal of Educational Measurement</searchLink>. Summer2017, Vol. 54 Issue 2, p184-199. 16p. – Name: Subject Label: Subject Terms Group: Su Data: *<searchLink fieldCode="DE" term="%22Item+response+theory%22">Item response theory</searchLink><br /><searchLink fieldCode="DE" term="%22Measurement+errors%22">Measurement errors</searchLink><br /><searchLink fieldCode="DE" term="%22Analysis+of+variance%22">Analysis of variance</searchLink><br /><searchLink fieldCode="DE" term="%22Arcsine+function%22">Arcsine function</searchLink><br /><searchLink fieldCode="DE" term="%22Distribution+%28Probability+theory%29%22">Distribution (Probability theory)</searchLink> – Name: Abstract Label: Abstract Group: Ab Data: The focus of this article is on scale score transformations that can be used to stabilize conditional standard errors of measurement (CSEMs). Three transformations for stabilizing the estimated CSEMs are reviewed, including the traditional arcsine transformation, a recently developed general variance stabilization transformation, and a new method proposed in this article involving cubic transformations. Two examples are provided and the three scale score transformations are compared in terms of how well they stabilize CSEMs estimated from compound binomial and item response theory (IRT) models. Advantages of the cubic transformation are demonstrated with respect to CSEM stabilization and other scaling criteria (e.g., scale score distributions that are more symmetric). [ABSTRACT FROM AUTHOR] – Name: AbstractSuppliedCopyright Label: Group: Ab Data: <i>Copyright of Journal of Educational Measurement is the property of Wiley-Blackwell 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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| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1111/jedm.12140 Languages: – Code: eng Text: English PhysicalDescription: Pagination: PageCount: 16 StartPage: 184 Subjects: – SubjectFull: Item response theory Type: general – SubjectFull: Measurement errors Type: general – SubjectFull: Analysis of variance Type: general – SubjectFull: Arcsine function Type: general – SubjectFull: Distribution (Probability theory) Type: general Titles: – TitleFull: Stabilizing Conditional Standard Errors of Measurement in Scale Score Transformations. Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Moses, Tim – PersonEntity: Name: NameFull: Kim, YoungKoung IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 06 Text: Summer2017 Type: published Y: 2017 Identifiers: – Type: issn-print Value: 00220655 Numbering: – Type: volume Value: 54 – Type: issue Value: 2 Titles: – TitleFull: Journal of Educational Measurement Type: main |
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