{"database":"biostudies-literature","file_versions":[],"scores":null,"additional":{"submitter":["Mansolf M"],"funding":["NIH Office of the Director","NIH HHS","Office of Behavioral and Social Sciences Research"],"pagination":["1121-1131"],"full_dataset_link":["https://www.ebi.ac.uk/biostudies/studies/S-EPMC10978247"],"repository":["biostudies-literature"],"omics_type":["Unknown"],"volume":["33(4)"],"pubmed_abstract":["<h4>Purpose</h4>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.<h4>Methods</h4>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.<h4>Results</h4>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.<h4>Conclusion</h4>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."],"journal":["Quality of life research : an international journal of quality of life aspects of treatment, care and rehabilitation"],"pubmed_title":["Assessing the interchangeability of linked scores in multivariable statistical analyses."],"pmcid":["PMC10978247"],"funding_grant_id":["U24OD023319","U24 OD023319"],"pubmed_authors":["Lai JS","Blackwell CK","Cella D","Mansolf M"],"additional_accession":[]},"is_claimable":false,"name":"Assessing the interchangeability of linked scores in multivariable statistical analyses.","description":"<h4>Purpose</h4>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.<h4>Methods</h4>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.<h4>Results</h4>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.<h4>Conclusion</h4>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.","dates":{"release":"2024-01-01T00:00:00Z","publication":"2024 Apr","modification":"2025-07-04T03:05:59.491Z","creation":"2025-07-04T03:05:59.491Z"},"accession":"S-EPMC10978247","cross_references":{"pubmed":["38294666"],"doi":["10.1007/s11136-023-03592-x"]}}