Assessing the interchangeability of linked scores in multivariable statistical analyses
- 31-01-2024
- Auteurs
- Maxwell Mansolf
- Courtney K. Blackwell
- David Cella
- Jin-Shei Lai
- Gepubliceerd in
- Quality of Life Research | Uitgave 4/2024
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.
- Titel
- Assessing the interchangeability of linked scores in multivariable statistical analyses
- Auteurs
-
Maxwell Mansolf
Courtney K. Blackwell
David Cella
Jin-Shei Lai
- Publicatiedatum
- 31-01-2024
- Uitgeverij
- Springer International Publishing
- Gepubliceerd in
-
Quality of Life Research / Uitgave 4/2024
Print ISSN: 0962-9343
Elektronisch ISSN: 1573-2649 - DOI
- https://doi.org/10.1007/s11136-023-03592-x
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Deze inhoud is alleen zichtbaar als je bent ingelogd en de juiste rechten hebt.
Deze inhoud is alleen zichtbaar als je bent ingelogd en de juiste rechten hebt.