A Bayesian model for time-to-event data with informative censoring
From MaRDI portal
Publication:3303820
DOI10.1093/biostatistics/kxr048zbMath1437.62508OpenAlexW2169525630WikidataQ34120218 ScholiaQ34120218MaRDI QIDQ3303820
Stevo Julius, Trivellore E. Raghunathan, Niko Kaciroti, Jeremy M. G. Taylor
Publication date: 4 August 2020
Published in: Biostatistics (Search for Journal in Brave)
Full work available at URL: http://europepmc.org/articles/pmc3297827
Related Items
A multi-treatment two stage adaptive allocation for survival outcomes, A Dirichlet process mixture model for non-ignorable dropout, A two-stage adaptive allocation design for survival outcome with informative censoring
Cites Work
- Nonparametric Bayes estimators based on beta processes in models for life history data
- Nonparametric Bayesian estimation of a survival curve with dependent censoring mechanism
- Estimation of survival curves from dependent censorship models via a generalized self-consistent property with nonparametric Bayesian estimation application
- Methods for Conducting Sensitivity Analysis of Trials with Potentially Nonignorable Competing Causes of Censoring
- Inference in Randomized Studies with Informative Censoring and Discrete Time-to-Event Endpoints
- Estimation and Comparison of Changes in the Presence of Informative Right Censoring by Modeling the Censoring Process
- A General Class of Pattern Mixture Models for Nonignorable Dropout with Many Possible Dropout Times
- Nonparametric Bayesian Estimation of Survival Curves from Incomplete Observations
- Monotone missing data and pattern‐mixture models
- Estimation of the failure time distribution in the presence of informative censoring
- Pattern-mixture models with proper time dependence
- A Random Pattern-Mixture Model for Longitudinal Data With Dropouts
- Reparameterizing the Pattern Mixture Model for Sensitivity Analyses Under Informative Dropout
- Pattern–Mixture and Selection Models for Analysing Longitudinal Data with Monotone Missing Patterns
- Pattern-Mixture Models for Multivariate Incomplete Data
- Estimates of marginal survival for dependent competing risks based on an assumed copula
- Modeling the Drop-Out Mechanism in Repeated-Measures Studies
- Incorporating prior beliefs about selection bias into the analysis of randomized trials with missing outcomes
- A Bayesian Approach for Clustered Longitudinal Ordinal Outcome With Nonignorable Missing Data