A Mover–Stayer Model for Longitudinal Marker Data

DOI10.1111/j.0006-341X.1999.01252.xzbMath1059.62615OpenAlexW2064681936WikidataQ30649874 ScholiaQ30649874MaRDI QIDQ4668344

Paul S. Albert

Publication date: 18 April 2005

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.0006-341x.1999.01252.x

zbMATH Keywords

incidenceprevalencehidden Markov modelsmeasurement errorthreshold models

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10)

Related Items (1)

Hidden Markov models for alcoholism treatment trial data

Cites Work

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• Random-Effects Models for Longitudinal Data
• Maximum Likelihood Estimation in the Mover-Stayer Model
• Identifiability of hidden Markov information sources and their minimum degrees of freedom
• Modeling Repeated Measures With Monotonic Ordinal Responses and Misclassification, With Applications to Studying Maturation
• Latent Variable Regression for Multiple Discrete Outcomes
• Repeated Probit Regression When Covariates Are Measured With Error
• Markov Chains With Measurement Error: Estimating the `True' Course of a Marker of the Progression of Human Immunodeficiency Virus Disease
• A Maximization Technique Occurring in the Statistical Analysis of Probabilistic Functions of Markov Chains
• On the Distribution of the Likelihood Ratio

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