Add to ORKGIn survival analyses, competing risks are encountered where the subjects under study are at risk for more than one mutually exclusive failure event [1]. Competing risks are often analysed using either cause-specific or subdistribution (cumulative incidence) proportional hazards models. Cause-specific hazards model the rate of occurrence of an event, whereas subdistribution hazards model the risk of failure of a specific event. Results of competing risks analyses are being presented more frequently in the medical literature, but the difference in the interpretation of various estimates, compared to standard Cox hazard ratios, is rarely considered
The analysis of survival or time-to-event data is one of the most common ap-plications of advanced s...
While nonparametric methods have been well established for inference on competing risks data, parame...
Background: In survival analysis, an event whose occurrence influences the occurrence of another eve...
In survival analyses, competing risks are encountered where the subjects under study are at risk for...
The possible occurrence of multiple events during follow-up is a common situation in several clinica...
Most clinical studies use conventional methods for survival analysis and calculate the risk of the e...
Item does not contain fulltextBACKGROUND: In studies of all-cause mortality, the fundamental epidemi...
Objective: Competing events are often ignored in epidemiological studies. Conventional methods for t...
The probability of an event occurring or the proportion of patients experiencing an event, such as d...
Competing risks data usually arises in studies in which the failure of an individual may be classifi...
In survival analysis, end of follow-up can be caused by the occurrence of the event of primary inter...
In survival analysis, the failure time of an event is interval-censored when the event is only known...
Background In studies of all-cause mortality, the fundamental epidemiological concepts of rate and r...
We consider a competing risks setting, when evaluating the prognostic influence of an exposure on a ...
Competing risk analysis refers to a special type of survival analysis that aims to correctly estimat...
The analysis of survival or time-to-event data is one of the most common ap-plications of advanced s...
While nonparametric methods have been well established for inference on competing risks data, parame...
Background: In survival analysis, an event whose occurrence influences the occurrence of another eve...
In survival analyses, competing risks are encountered where the subjects under study are at risk for...
The possible occurrence of multiple events during follow-up is a common situation in several clinica...
Most clinical studies use conventional methods for survival analysis and calculate the risk of the e...
Item does not contain fulltextBACKGROUND: In studies of all-cause mortality, the fundamental epidemi...
Objective: Competing events are often ignored in epidemiological studies. Conventional methods for t...
The probability of an event occurring or the proportion of patients experiencing an event, such as d...
Competing risks data usually arises in studies in which the failure of an individual may be classifi...
In survival analysis, end of follow-up can be caused by the occurrence of the event of primary inter...
In survival analysis, the failure time of an event is interval-censored when the event is only known...
Background In studies of all-cause mortality, the fundamental epidemiological concepts of rate and r...
We consider a competing risks setting, when evaluating the prognostic influence of an exposure on a ...
Competing risk analysis refers to a special type of survival analysis that aims to correctly estimat...
The analysis of survival or time-to-event data is one of the most common ap-plications of advanced s...
While nonparametric methods have been well established for inference on competing risks data, parame...
Background: In survival analysis, an event whose occurrence influences the occurrence of another eve...