A latent class linear mixed model for monotonic continuous processes measured with error

Motivated by measurement errors in radiographic diagnosis of osteoarthritis, we propose a Bayesian approach to identify latent classes in a model with continuous response subject to a monotonic, that is, non-decreasing or non-increasing, process with measurement error. A latent class linear mixed mo...

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Bibliographic Details
Published inStatistical methods in medical research Vol. 33; no. 3; pp. 449 - 464
Main Authors Espin-Garcia, Osvaldo, Naranjo, Lizbeth, Fuentes-García, Ruth
Format Journal Article
LanguageEnglish
Published London, England SAGE Publications 01.03.2024
Subjects
disease trajectories
latent class linear mixed models
measurement error
monotonic continuous process
Bayesian analysis
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Summary:Motivated by measurement errors in radiographic diagnosis of osteoarthritis, we propose a Bayesian approach to identify latent classes in a model with continuous response subject to a monotonic, that is, non-decreasing or non-increasing, process with measurement error. A latent class linear mixed model has been introduced to consider measurement error while the monotonic process is accounted for via truncated normal distributions. The main purpose is to classify the response trajectories through the latent classes to better describe the disease progression within homogeneous subpopulations.
ISSN:0962-2802
1477-0334
DOI:10.1177/09622802231225963