Efficient Estimation in the Fine and Gray Model
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Publication:6144763
DOI10.1080/01621459.2022.2057860OpenAlexW4220920396MaRDI QIDQ6144763
Thomas H. Scheike, Torben Martinussen, Brice Maxime Hugues Ozenne
Publication date: 8 January 2024
Published in: Journal of the American Statistical Association (Search for Journal in Brave)
Full work available at URL: https://figshare.com/articles/journal_contribution/Efficient_estimation_in_the_Fine_and_Gray_model/19426685
efficient estimationcensoringcounting processesdouble robustnessinverse probability of censoring weightingFine-Gray model
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Cites Work
- Unified methods for censored longitudinal data and causality
- Semiparametric theory and missing data.
- A Proportional Hazards Regression Model for the Subdistribution with Covariates-adjusted Censoring Weight for Competing Risks Data
- The proportional odds cumulative incidence model for competing risks
- Cause-Specific Cumulative Incidence Estimation and the Fine and Gray Model Under Both Left Truncation and Right Censoring
- On the estimation of average treatment effects with right‐censored time to event outcome and competing risks
- Predicting cumulative incidence probability by direct binomial regression
- Regression modeling of competing crude failure probabilities
- Generalised linear models for correlated pseudo-observations, with applications to multi-state models
- A Proportional Hazards Model for the Subdistribution of a Competing Risk
- Prediction of Cumulative Incidence Function under the Proportional Hazards Model
- Analysing Competing Risks Data With Transformation Models
- Efficient Estimation of Semiparametric Transformation Models for the Cumulative Incidence of Competing Risks
- Regression Modeling of Competing Risks Data Based on Pseudovalues of the Cumulative Incidence Function
- Statistical models based on counting processes
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