Modeling of Multivariate Monotone Disease Processes in the Presence of Misclassification

DOI10.1080/01621459.2012.682804zbMath1395.62339OpenAlexW2113826455MaRDI QIDQ4648540

Guillermo Marshall, María José García-Zattera, Alejandro Jara, Emmanuel Lesaffre

Publication date: 9 November 2012

Published in: Journal of the American Statistical Association (Search for Journal in Brave)

Full work available at URL: http://hdl.handle.net/10533/133090

zbMATH Keywords

hidden Markov modelmisclassificationmultivariate binary dataincidence estimationmonotone binary processes

Mathematics Subject Classification ID

Estimation in multivariate analysis (62H12) Applications of statistics to biology and medical sciences; meta analysis (62P10) Markov processes: estimation; hidden Markov models (62M05)

Related Items

Repeated responses in misclassification binary regression: A Bayesian approach, A flexible AFT model for misclassified clustered interval‐censored data, Fully Nonparametric Regression Modelling of Misclassified Censored Time-to-Event Data, Multivariate longitudinal data analysis with mixed effects hidden Markov models, Semiparametric time to event models in the presence of error-prone, self-reported outcomes -- with application to the women's health initiative, Oral health research: A source for innovative new statistical developments, Marginal Bayesian Semiparametric Modeling of Mismeasured Multivariate Interval-Censored Data, Skewed link-based regression models for misclassified binary data, Interval-censored data with misclassification: a Bayesian approach

Uses Software

• R

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