Competing Risks and Time-Dependent Covariates

DOI10.1002/bimj.200900076zbMath1207.62087OpenAlexW2021100796WikidataQ45714753 ScholiaQ45714753MaRDI QIDQ2786158

Giuliana Cortese, Per Kragh Andersen

Publication date: 21 September 2010

Published in: Biometrical Journal (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1002/bimj.200900076

zbMATH Keywords

competing riskscumulative incidence functionmulti-state modelsinternal time-dependent covariatessemi-parametric regression models

Mathematics Subject Classification ID

Nonparametric regression and quantile regression (62G08) Applications of statistics to biology and medical sciences; meta analysis (62P10) Inference from stochastic processes (62M99) Estimation in survival analysis and censored data (62N02) Markov processes (60J99)

Related Items (13)

Dynamic prediction of mortality among patients in intensive care using the sequential organ failure assessment (SOFA) score: a joint competing risk survival and longitudinal modeling approach ⋮ Hazards regression for freemium products and services: a competing risks approach ⋮ Regression analysis of competing risks data via semi-parametric additive hazard model ⋮ Semiparametric regression and risk prediction with competing risks data under missing cause of failure ⋮ A general piecewise multi-state survival model: application to breast cancer ⋮ Analysis of interval censored failure time data with competing risk ⋮ Incorporating short‐term outcome information to predict long‐term survival with discrete markers ⋮ Application of multistate models in hospital epidemiology: Advances and challenges ⋮ Dynamic Pseudo‐Observations: A Robust Approach to Dynamic Prediction in Competing Risks ⋮ Hans van Houwelingen, 40 Years in Biostatistics ⋮ Estimating summary functionals in multistate models with an application to hospital infection data ⋮ Quantifying the predictive accuracy of time-to-event models in the presence of competing risks ⋮ Time-Dependent AUC with Right-Censored Data: A Survey

Uses Software

• cmprsk

Cites Work

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• A class of k-sample tests for comparing the cumulative incidence of a competing risk
• The Analysis of Failure Times in the Presence of Competing Risks
• An Additive–Multiplicative Cox–Aalen Regression Model
• A Proportional Hazards Model for the Subdistribution of a Competing Risk
• Competing risks as a multi-state model
• Dynamic Prediction by Landmarking in Event History Analysis
• Additive hazards Markov regression models illustrated with bone marrow transplant data
• Statistical models based on counting processes

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