Modeling potential time to event data with competing risks
نویسندگان
چکیده
منابع مشابه
Boosting for high-dimensional time-to-event data with competing risks
MOTIVATION For analyzing high-dimensional time-to-event data with competing risks, tailored modeling techniques are required that consider the event of interest and the competing events at the same time, while also dealing with censoring. For low-dimensional settings, proportional hazards models for the subdistribution hazard have been proposed, but an adaptation for high-dimensional settings i...
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background & aim: we aimed to describe a standard survival analysis, so that we can analyze some factors related to the time of occurrence of different types of reflux (unilateral-left, unilateralright, and bilateral) in children with antenatal hydronephrosis (anh) and to provide an approach taking competing risks into account. methods & materials: we used data of 193 children that was collecte...
متن کاملSemi-Competing Risks Data Analysis
Hospital readmission is a key marker of quality of healthcare; it has been used to investigate variation in quality among patients in a broad range of clinical contexts and has become an important policy measure. Notwithstanding its widespread use, however, readmission remains controversial as a measure of quality. Among the concerns raised, whether and how patient deaths are handled in the ana...
متن کاملImpact of the censoring distribution on time-to-event problems in the presence of competing risks
Objectives Methods accounting for competing risks in time-to-event problems are becoming common in mainstream statistical analyses. Standard approaches include those based on log-rank type tests [1] and cumulative incidence regression [2]. These approaches are based on weighting competing events by the censoring distribution. The usual cumulative incidence regression uses weights based on the p...
متن کاملQuantifying the predictive accuracy of time-to-event models in the presence of competing risks.
Prognostic models for time-to-event data play a prominent role in therapy assignment, risk stratification and inter-hospital quality assurance. The assessment of their prognostic value is vital not only for responsible resource allocation, but also for their widespread acceptance. The additional presence of competing risks to the event of interest requires proper handling not only on the model ...
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ژورنال
عنوان ژورنال: Lifetime Data Analysis
سال: 2013
ISSN: 1380-7870,1572-9249
DOI: 10.1007/s10985-013-9279-z