scholarly journals Validation of discrete time‐to‐event prediction models in the presence of competing risks

2019 ◽  
Vol 62 (3) ◽  
pp. 643-657 ◽  
Author(s):  
Rachel Heyard ◽  
Jean‐François Timsit ◽  
Leonhard Held ◽  
Keyword(s):  
Competing Risks ◽  
Discrete Time ◽  
Prediction Models ◽  
Time To Event ◽  
Event Prediction

Dynamic clinical prediction models for discrete time‐to‐event data with competing risks—A case study on the OUTCOMEREA database

2018 ◽  
Vol 61 (3) ◽  
pp. 514-534 ◽  
Author(s):  
Rachel Heyard ◽  
Jean‐François Timsit ◽  
Wafa Ibn Essaied ◽  
Leonhard Held ◽  
Keyword(s):  
Competing Risks ◽  
Discrete Time ◽  
Prediction Models ◽  
Event Data ◽  
Clinical Prediction ◽  
Time To Event ◽  
Clinical Prediction Models ◽  
Time To Event Data

scholarly journals Modeling potential time to event data with competing risks

2013 ◽  
Vol 20 (2) ◽  
pp. 316-334 ◽  
Author(s):  
Liang Li ◽  
Bo Hu ◽  
Michael W. Kattan
Keyword(s):  
Competing Risks ◽  
Event Data ◽  
Time To Event ◽  
Time To Event Data

scholarly journals Quantifying the predictive accuracy of time-to-event models in the presence of competing risks

2011 ◽  
Vol 53 (1) ◽  
pp. 88-112 ◽  
Author(s):  
Rotraut Schoop ◽  
Jan Beyersmann ◽  
Martin Schumacher ◽  
Harald Binder
Keyword(s):  
Competing Risks ◽  
Predictive Accuracy ◽  
Time To Event ◽  
Event Models

Survival analysis

2020 ◽  
pp. 181-218
Author(s):  
Bendix Carstensen
Keyword(s):  
Survival Analysis ◽  
Competing Risks ◽  
Cox Model ◽  
Survival Function ◽  
Event Analysis ◽  
Time To Event ◽  
Poisson Models ◽  
Kaplan Meier ◽  
Analysis Survival ◽  
Event Rates

This chapter describes survival analysis. Survival analysis concerns data where the outcome is a length of time, namely the time from inclusion in the study (such as diagnosis of some disease) till death or some other event — hence the term 'time to event analysis', which is also used. There are two primary targets normally addressed in survival analysis: survival probabilities and event rates. The chapter then looks at the life table estimator of survival function and the Kaplan–Meier estimator of survival. It also considers the Cox model and its relationship with Poisson models, as well as the Fine–Gray approach to competing risks.

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