A Framework for the Joint Modeling of Longitudinal Diagnostic Outcome Data and Latent Infection Status: Application to Investigating the Temporal Relationship between Infection and Disease

DOI10.1111/j.1541-0420.2011.01687.xzbMath1251.62045OpenAlexW2108764979WikidataQ34049553 ScholiaQ34049553MaRDI QIDQ2912328

W. D. Vink, Wesley O. Johnson, Nigel P. French, Geoffrey Jones

Publication date: 14 September 2012

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.1541-0420.2011.01687.x

zbMATH Keywords

sensitivityBayesian statisticsspecificityMCMCdiagnostic testbiomarkerslatent variable modelingbovine digital dermatitis

Mathematics Subject Classification ID

Related Items (3)

Biomarker assessment and combination with differential covariate effects and an unknown gold standard, with an application to Alzheimer's disease ⋮ Bayesian modeling of temporal properties of infectious disease in a college student population ⋮ Model-based clustering for assessing the prognostic value of imaging biomarkers and mixed type tests

Cites Work

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• Modeling bivariate longitudinal diagnostic outcome data in the absence of a gold standard
• Evaluation of the accuracy of diagnostic tests from repeated~measurements~without a~gold~standard
• Missing responses in generalised linear mixed models when the missing data mechanism is nonignorable
• Identifiability of Models for Multiple Diagnostic Testing in the Absence of a Gold Standard
• Modeling Disease Progression With Longitudinal Markers
• Latent Variable Modeling of Diagnostic Accuracy
• Estimation of Operating Characteristics for Dependent Diagnostic Tests Based on Latent Markov Models

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