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Assessing the interchangeability of linked scores in multivariable statistical analyses.

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Title: Assessing the interchangeability of linked scores in multivariable statistical analyses.
Authors: Mansolf, Maxwell (AUTHOR), Blackwell, Courtney K. (AUTHOR), Cella, David (AUTHOR), Lai, Jin-Shei (AUTHOR)
Source: Quality of Life Research. Apr2024, Vol. 33 Issue 4, p1121-1131. 11p.
Subjects: Classical test theory, Structural equation modeling, Statistics, Multivariable testing, Generalizability theory, World health
Abstract: Purpose: Using the lens of classical test theory, we examine a linkage's generalizability with respect to use in multivariable analyses, including multiple regression and structural equation modeling, rather than comparison of established subpopulations as is most common in the literature. Methods: To aid in this evaluation, we present a structural-equation-modeling based statistical method to examine the suitability of a given linkage for use cases involving continuous and categorical variables external to the linkage itself. Results: Using the PROMIS® Parent Proxy and Early Childhood Global Health measures, we show that, although a high correlation between the scores (here, r =.829) may imply a general suitability for linking, a more detailed investigation of content, measurement structure, and results of the proposed methodology reveal important differences between the measures which can compromise interchangeability in certain use cases. Conclusion: In addition to the statistical quality of a linkage, users of linking methodology should also assess the question of whether the linkage is appropriate to apply to particular use cases of interest. [ABSTRACT FROM AUTHOR]
Copyright of Quality of Life Research is the property of Springer Nature 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: Assessing the interchangeability of linked scores in multivariable statistical analyses.
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  Data: <searchLink fieldCode="AR" term="%22Mansolf%2C+Maxwell%22">Mansolf, Maxwell</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Blackwell%2C+Courtney+K%2E%22">Blackwell, Courtney K.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Cella%2C+David%22">Cella, David</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Lai%2C+Jin-Shei%22">Lai, Jin-Shei</searchLink> (AUTHOR)
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  Data: Purpose: Using the lens of classical test theory, we examine a linkage's generalizability with respect to use in multivariable analyses, including multiple regression and structural equation modeling, rather than comparison of established subpopulations as is most common in the literature. Methods: To aid in this evaluation, we present a structural-equation-modeling based statistical method to examine the suitability of a given linkage for use cases involving continuous and categorical variables external to the linkage itself. Results: Using the PROMIS® Parent Proxy and Early Childhood Global Health measures, we show that, although a high correlation between the scores (here, r =.829) may imply a general suitability for linking, a more detailed investigation of content, measurement structure, and results of the proposed methodology reveal important differences between the measures which can compromise interchangeability in certain use cases. Conclusion: In addition to the statistical quality of a linkage, users of linking methodology should also assess the question of whether the linkage is appropriate to apply to particular use cases of interest. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Quality of Life Research is the property of Springer Nature 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: Apr2024
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