Assessing the interchangeability of linked scores in multivariable statistical analyses.

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.