A new approach to regression analysis of censored competing-risks data
From MaRDI portal
Publication:1641904
DOI10.1007/s10985-016-9378-8zbMath1468.62361OpenAlexW2477479196WikidataQ36097798 ScholiaQ36097798MaRDI QIDQ1641904
Publication date: 20 June 2018
Published in: Lifetime Data Analysis (Search for Journal in Brave)
Full work available at URL: http://europepmc.org/articles/pmc5299091
asymptotic efficiencycumulative incidence functionVolterra equationmartingale central limit theoremempirical process theoryhazard function of subdistributionsemiparametric likelihood
Applications of statistics to biology and medical sciences; meta analysis (62P10) Estimation in survival analysis and censored data (62N02)
Uses Software
Cites Work
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Unnamed Item
- Pseudo-observations for competing risks with covariate dependent censoring
- On pseudo-values for regression analysis in competing risks models
- Case-control survival analysis with a general semiparametric shared frailty model: A pseudo full likelihood approach
- A class of k-sample tests for comparing the cumulative incidence of a competing risk
- Large sample theory of a modified Buckley-James estimator for regression analysis with censored data
- A missing information principle and \(M\)-estimators in regression analysis with censored and truncated data
- Stochastic integrals of empirical-type processes with applications to censored regression
- Pseudo-full likelihood estimation for prospective survival analysis with a general semiparametric shared frailty model: Asymptotic theory
- Cause-Specific Cumulative Incidence Estimation and the Fine and Gray Model Under Both Left Truncation and Right Censoring
- The Aalen additive gamma frailty hazards model
- Predicting cumulative incidence probability by direct binomial regression
- Asymptotic Statistics
- A Proportional Hazards Model for the Subdistribution of a Competing Risk
- Multi-state models for bone marrow transplantation studies
- Regression Modeling of Competing Risks Data Based on Pseudovalues of the Cumulative Incidence Function
- A Pseudo–Partial Likelihood Method for Semiparametric Survival Regression With Covariate Errors
- Statistical models based on counting processes
This page was built for publication: A new approach to regression analysis of censored competing-risks data