Discrete‐Time Nonparametric Estimation for Semi‐Markov Models of Chain‐of‐Events Data Subject to Interval Censoring and Truncation

DOI10.1111/j.0006-341X.1999.00514.xzbMath1059.62719OpenAlexW1982395631WikidataQ30650149 ScholiaQ30650149MaRDI QIDQ4666598

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.1999.00514.x

zbMATH Keywords

truncationEM algorithminterval censoringHIV/AIDSself-consistent estimatorchain-of-events datamultistage modelsemi-Markov assumption

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Nonparametric estimation (62G05) Applications of Markov renewal processes (reliability, queueing networks, etc.) (60K20)

Related Items (12)

Semi-Markov Models for Multistate Data Analysis with Periodic Observations ⋮ Semiparametric time‐to‐event modeling in the presence of a latent progression event ⋮ Parametric inference for time-to-failure in multi-state semi-Markov models: A comparison of marginal and process approaches ⋮ Earthquakes occurrences estimation through a parametric semi-Markov approach ⋮ A stochastic model for the HIV/AIDS dynamic evolution ⋮ Past states of continuous-time Markov models for ecological communities ⋮ Fitting Semi‐Markov Models to Interval‐Censored Data with Unknown Initiation Times ⋮ Estimating the Extent of Tracking in Interval‐Censored Chain‐Of‐Events Data ⋮ The S-U algorithm for missing data problems ⋮ Analysis of Functional Status Transitions by Using a Semi-Markov Process Model in the Presence of Left-Censored Spells ⋮ Nonparametric inference and uniqueness for periodically observed progressive disease models ⋮ On Nonparametric Maximum Likelihood Estimation with Interval Censoring and Left Truncation

Cites Work

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• Analysis of Doubly-Censored Survival Data, with Application to AIDS
• The Analysis of Panel Data Under a Markov Assumption
• A Markov Model for Analysing Cancer Markers and Disease States in Survival Studies
• Inference Based on Retrospective Ascertainment: An Analysis of the Data on Transfusion-Related AIDS
• The Analysis of Retrospectively Ascertained Data in the Presence of Reporting Delays
• Semi-Markov models for partially censored data

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