Journal Article

DZNE-2025-00731

http://join2-wiki.gsi.de/foswiki/pub/Main/Artwork/join2_logo100x88.png Modeling the ratio of correlated biomarkers using copula regression.

Berger, M. ; Klein, N. ; Wagner, M.DZNE* ; Schmid, M.Extern*

2025
Sage London [u.a.]

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Please use a persistent id in citations: doi:10.1177/09622802241313293

Abstract: Modeling the ratio of two dependent components as a function of covariates is a frequently pursued objective in observational research. Despite the high relevance of this topic in medical studies, where biomarker ratios are often used as surrogate endpoints for specific diseases, existing models are commonly based on oversimplified assumptions, assuming e.g. independence or strictly positive associations between the components. In this paper, we overcome such limitations and propose a regression model where the marginal distributions of the two components are linked by a copula. A key feature of our model is that it allows for both positive and negative associations between the components, with one of the model parameters being directly interpretable in terms of Kendall's rank correlation coefficient. We study our method theoretically, evaluate finite sample properties in a simulation study and demonstrate its efficacy in an application to diagnosis of Alzheimer's disease via ratios of amyloid-beta and total tau protein biomarkers.

Keyword(s): Biomarkers (MeSH) ; Humans (MeSH) ; Alzheimer Disease: diagnosis (MeSH) ; Amyloid beta-Peptides (MeSH) ; tau Proteins (MeSH) ; Models, Statistical (MeSH) ; Regression Analysis (MeSH) ; Computer Simulation (MeSH) ; Copula model ; distributional regression ; gamma distribution ; negative dependence ; ratio outcome ; Biomarkers ; Amyloid beta-Peptides ; tau Proteins

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Contributing Institute(s):

1. Neuropsychology (AG Wagner)

Research Program(s):

1. 353 - Clinical and Health Care Research (POF4-353) (POF4-353)

Appears in the scientific report 2025

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Database coverage:
; ; ; Clarivate Analytics Master Journal List ; Current Contents - Clinical Medicine ; Ebsco Academic Search ; Essential Science Indicators ; IF < 5 ; JCR ; National-Konsortium ; SCOPUS ; Science Citation Index Expanded ; Web of Science Core Collection

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