A Quantitative Method for Evaluating the Predictive Utility of Linked Scores
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| Title: | A Quantitative Method for Evaluating the Predictive Utility of Linked Scores |
|---|---|
| Language: | English |
| Authors: | Yoshikazu Sato (ORCID |
| Source: | Journal of Educational Measurement. 2025 62(4):907-928. |
| Availability: | Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us |
| Peer Reviewed: | Y |
| Page Count: | 22 |
| Publication Date: | 2025 |
| Document Type: | Journal Articles Reports - Research |
| Education Level: | Higher Education Postsecondary Education |
| Descriptors: | College Entrance Examinations, Prediction, Monte Carlo Methods, Law Schools, Equated Scores, Accountability |
| Assessment and Survey Identifiers: | ACT Assessment, SAT (College Admission Test), Law School Admission Test |
| DOI: | 10.1111/jedm.70018 |
| ISSN: | 0022-0655 1745-3984 |
| Abstract: | In U.S. colleges, admissions officers tend to use ACT-SAT concordant scores, also known as linked scores, as predictions of individual scores for tests not taken. The major problem in this situation is the use of linked scores without thoroughly examining their predictive utility (i.e., the degree to which they serve as predicted scores at the individual level). To address this problem, we developed a method, referred to as the "predictive utility analysis," for quantitatively evaluating the prediction accuracy and error properties of linked scores. A Monte Carlo simulation provided several findings on the behavior of the indices formulated in this paper regarding the number of common examinees, the number of items, and the correlation between tests. Furthermore, we illustrated the predictive utility analysis in concordance and equating with the results of an actual large-scale test, the Japan Law School Admission Test. In both examples, we found that the linked scores obtained by using the equipercentile or linear equating method could be used as predictions of individual scores. Our findings suggest that the predictive utility analysis offers practical guidance for enhancing the use of linked scores as well as supporting institutional accountability. |
| Abstractor: | As Provided |
| Entry Date: | 2026 |
| Accession Number: | EJ1491553 |
| Database: | ERIC |
| FullText | Text: Availability: 0 |
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| Header | DbId: eric DbLabel: ERIC An: EJ1491553 AccessLevel: 3 PubType: Academic Journal PubTypeId: academicJournal PreciseRelevancyScore: 0 |
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| Items | – Name: Title Label: Title Group: Ti Data: A Quantitative Method for Evaluating the Predictive Utility of Linked Scores – Name: Language Label: Language Group: Lang Data: English – Name: Author Label: Authors Group: Au Data: <searchLink fieldCode="AR" term="%22Yoshikazu+Sato%22">Yoshikazu Sato</searchLink> (ORCID <externalLink term="https://orcid.org/0000-0003-4290-0720">0000-0003-4290-0720</externalLink>)<br /><searchLink fieldCode="AR" term="%22Tadashi+Shibayama%22">Tadashi Shibayama</searchLink> – Name: TitleSource Label: Source Group: Src Data: <searchLink fieldCode="SO" term="%22Journal+of+Educational+Measurement%22"><i>Journal of Educational Measurement</i></searchLink>. 2025 62(4):907-928. – Name: Avail Label: Availability Group: Avail Data: Wiley. Available from: John Wiley & Sons, Inc. 111 River Street, Hoboken, NJ 07030. Tel: 800-835-6770; e-mail: cs-journals@wiley.com; Web site: https://www.wiley.com/en-us – Name: PeerReviewed Label: Peer Reviewed Group: SrcInfo Data: Y – Name: Pages Label: Page Count Group: Src Data: 22 – Name: DatePubCY Label: Publication Date Group: Date Data: 2025 – Name: TypeDocument Label: Document Type Group: TypDoc Data: Journal Articles<br />Reports - Research – Name: Audience Label: Education Level Group: Audnce Data: <searchLink fieldCode="EL" term="%22Higher+Education%22">Higher Education</searchLink><br /><searchLink fieldCode="EL" term="%22Postsecondary+Education%22">Postsecondary Education</searchLink> – Name: Subject Label: Descriptors Group: Su Data: <searchLink fieldCode="DE" term="%22College+Entrance+Examinations%22">College Entrance Examinations</searchLink><br /><searchLink fieldCode="DE" term="%22Prediction%22">Prediction</searchLink><br /><searchLink fieldCode="DE" term="%22Monte+Carlo+Methods%22">Monte Carlo Methods</searchLink><br /><searchLink fieldCode="DE" term="%22Law+Schools%22">Law Schools</searchLink><br /><searchLink fieldCode="DE" term="%22Equated+Scores%22">Equated Scores</searchLink><br /><searchLink fieldCode="DE" term="%22Accountability%22">Accountability</searchLink> – Name: SubjectThesaurus Label: Assessment and Survey Identifiers Group: Su Data: <searchLink fieldCode="SU" term="%22ACT+Assessment%22">ACT Assessment</searchLink><br /><searchLink fieldCode="SU" term="%22SAT+%28College+Admission+Test%29%22">SAT (College Admission Test)</searchLink><br /><searchLink fieldCode="SU" term="%22Law+School+Admission+Test%22">Law School Admission Test</searchLink> – Name: DOI Label: DOI Group: ID Data: 10.1111/jedm.70018 – Name: ISSN Label: ISSN Group: ISSN Data: 0022-0655<br />1745-3984 – Name: Abstract Label: Abstract Group: Ab Data: In U.S. colleges, admissions officers tend to use ACT-SAT concordant scores, also known as linked scores, as predictions of individual scores for tests not taken. The major problem in this situation is the use of linked scores without thoroughly examining their predictive utility (i.e., the degree to which they serve as predicted scores at the individual level). To address this problem, we developed a method, referred to as the "predictive utility analysis," for quantitatively evaluating the prediction accuracy and error properties of linked scores. A Monte Carlo simulation provided several findings on the behavior of the indices formulated in this paper regarding the number of common examinees, the number of items, and the correlation between tests. Furthermore, we illustrated the predictive utility analysis in concordance and equating with the results of an actual large-scale test, the Japan Law School Admission Test. In both examples, we found that the linked scores obtained by using the equipercentile or linear equating method could be used as predictions of individual scores. Our findings suggest that the predictive utility analysis offers practical guidance for enhancing the use of linked scores as well as supporting institutional accountability. – Name: AbstractInfo Label: Abstractor Group: Ab Data: As Provided – Name: DateEntry Label: Entry Date Group: Date Data: 2026 – Name: AN Label: Accession Number Group: ID Data: EJ1491553 |
| PLink | https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=eric&AN=EJ1491553 |
| RecordInfo | BibRecord: BibEntity: Identifiers: – Type: doi Value: 10.1111/jedm.70018 Languages: – Text: English PhysicalDescription: Pagination: PageCount: 22 StartPage: 907 Subjects: – SubjectFull: College Entrance Examinations Type: general – SubjectFull: Prediction Type: general – SubjectFull: Monte Carlo Methods Type: general – SubjectFull: Law Schools Type: general – SubjectFull: Equated Scores Type: general – SubjectFull: Accountability Type: general – SubjectFull: ACT Assessment Type: general – SubjectFull: SAT (College Admission Test) Type: general – SubjectFull: Law School Admission Test Type: general Titles: – TitleFull: A Quantitative Method for Evaluating the Predictive Utility of Linked Scores Type: main BibRelationships: HasContributorRelationships: – PersonEntity: Name: NameFull: Yoshikazu Sato – PersonEntity: Name: NameFull: Tadashi Shibayama IsPartOfRelationships: – BibEntity: Dates: – D: 01 M: 12 Type: published Y: 2025 Identifiers: – Type: issn-print Value: 0022-0655 – Type: issn-electronic Value: 1745-3984 Numbering: – Type: volume Value: 62 – Type: issue Value: 4 Titles: – TitleFull: Journal of Educational Measurement Type: main |
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