Fitting Semi‐Markov Models to Interval‐Censored Data with Unknown Initiation Times

DOI10.1111/j.0006-341X.1999.00507.xzbMath1059.62706OpenAlexW2006632973WikidataQ30650146 ScholiaQ30650146MaRDI QIDQ4666597

Glen A. Satten, Maya R. Sternberg

Publication date: 13 April 2005

Published in: Biometrics (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1111/j.0006-341x.1999.00507.x

zbMATH Keywords

truncationEM algorithminterval censoringleft censoringdoubly censored dataHIV/AIDSsemi-Markov modelmultistage modelcahin-of-events datainitiation time

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05) Markov renewal processes, semi-Markov processes (60K15)

Related Items (7)

Earthquakes occurrences estimation through a parametric semi-Markov approach ⋮ Parametric and non homogeneous semi-Markov process for HIV control ⋮ A stochastic model for the HIV/AIDS dynamic evolution ⋮ Estimating the Extent of Tracking in Interval‐Censored Chain‐Of‐Events Data ⋮ Semi-Markov Models with Phase-Type Sojourn Distributions ⋮ The semi-Markov beta-Stacy process: a Bayesian non-parametric prior for semi-Markov processes. ⋮ Estimation and assessment of Markov multistate models with intermittent observations on individuals

Cites Work

• Analysis of Doubly-Censored Survival Data, with Application to AIDS
• The Analysis of Panel Data Under a Markov Assumption
• Semi-Markov models for partially censored data
• Discrete‐Time Nonparametric Estimation for Semi‐Markov Models of Chain‐of‐Events Data Subject to Interval Censoring and Truncation
• Unnamed Item

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