A multistate joint model for interval-censored event-history data subject to within-unit clustering and informative missingness, with application to neurocysticercosis research
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Publication:6627601
DOI10.1002/sim.8663zbMATH Open1546.629MaRDI QIDQ6627601
W. Allen Hauser, Hong Bin Zhang, Arturo Carpio, Elizabeth A. Kelvin
Publication date: 29 October 2024
Published in: Statistics in Medicine (Search for Journal in Brave)
nonignorable missingnessinterval-censoringfrailty survival modelmultistate joint modelneurocysticercosis
Cites Work
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- The Analysis of Panel Data Under a Markov Assumption
- Missing Covariates in Generalized Linear Models When the Missing Data Mechanism is Non-ignorable
- Maximizing Generalized Linear Mixed Model Likelihoods With an Automated Monte Carlo EM Algorithm
- Markov Chains
- Mixed Effects Logistic Regression Models for Longitudinal Binary Response Data with Informative Drop-Out
- Fitting Semi‐Markov Models to Interval‐Censored Data with Unknown Initiation Times
- Markov Chains With Measurement Error: Estimating the `True' Course of a Marker of the Progression of Human Immunodeficiency Virus Disease
- Adaptive Rejection Sampling for Gibbs Sampling
- An Approximate Generalized Linear Model with Random Effects for Informative Missing Data
- A multistate model for correlated interval-censored life history data in caries research
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Modeling the multi-state natural history of rare diseases with heterogeneous individual patient data: a simulation study ⋮ A discrete approximation method for modeling interval-censored multistate data ⋮ Joint modeling of multistate and nonparametric multivariate longitudinal data
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