Simple analysis of non-Markov models: A case study on heart transplant data
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Publication:4971404
DOI10.1177/1471082X14535528MaRDI QIDQ4971404
Dimitris Rizopoulos, Magdalena Murawska
Publication date: 12 October 2020
Published in: Statistical Modelling (Search for Journal in Brave)
Cites Work
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- Longitudinal data analysis using generalized linear models
- On pseudo-values for regression analysis in competing risks models
- Validity of the Aalen-Johansen estimators of stage occupation probabilities and Nelson-Aalen estimators of integrated transition hazards for non-Markov models
- Regression analysis of restricted mean survival time based on pseudo-observations
- The jackknife and bootstrap
- Marginal Models for Clustered Time-to-Event Data with Competing Risks Using Pseudovalues
- Robust Inference for Event Probabilities with Non-Markov Event Data
- Estimation of Integrated Transition Hazards and Stage Occupation Probabilities for Non-Markov Systems Under Dependent Censoring
- Variance estimation for the jackknife using von Mises expansions
- Nonparametric Estimation of Stage Occupation Probabilities in a Multistage Model with Current Status Data
- A Conditional Markov Model for Clustered Progressive Multistate Processes under Incomplete Observation
- Generalised linear models for correlated pseudo-observations, with applications to multi-state models
- Regression Analysis for Multistate Models Based on a Pseudo‐value Approach, with Applications to Bone Marrow Transplantation Studies
- A penalized likelihood approach for an illness-death model with interval-censored data: application to age-specific incidence of dementia
- Regression Modeling of Competing Risks Data Based on Pseudovalues of the Cumulative Incidence Function
- Statistical models based on counting processes
- Nonparametric estimation of transition probabilities in a non-Markov illness-death model
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