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Latent class models for joint analysis of disease prevalence and high-dimensional semicontinuous biomarker data

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Publication:2893220
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DOI10.1093/biostatistics/kxr024zbMath1239.62143OpenAlexW2114776556WikidataQ34016049 ScholiaQ34016049MaRDI QIDQ2893220

Paul S. Albert, Zhen Chen, Bo Zhang

Publication date: 26 June 2012

Published in: Biostatistics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1093/biostatistics/kxr024


zbMATH Keywords

random effectslatent variablescategorical dataMonte Carlo EM algorithmchemical exposure biomarkers


Mathematics Subject Classification ID

Lua error in Module:PublicationMSCList at line 37: attempt to index local 'msc_result' (a nil value).


Related Items (2)

A latent functional approach for modeling the effects of multidimensional exposures on disease risk ⋮ Composite likelihood and maximum likelihood methods for joint latent class modeling of disease prevalence and high-dimensional semicontinuous biomarker data




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