CITATION:Haushona N, Esterhuizen TM, Thabane L, Machekano R. An empirical comparison of time-to-event models to analyse a composite outcome in the presence of death as a competing risk. Contemp Clin Trials Commun. 2020;19:100639. Published 2020 Aug 14. doi:10.1016/j.conctc.2020.100639Introduction: Competing risks arise when subjects are exposed to multiple mutually exclusive failure events, and the occurrence of one failure hinders the occurrence of other failure events. In the presence of competing risks, it is important to use methods accounting for competing events because failure to account for these events might result in misleading inferences. Methods and Objective: Using data from a multisite retrospective observational longitudi...
Competing events can preclude the event of interest from occurring in epidemiologic data and can be ...
Clinical trials and cohort studies that collect survival data frequently involve patients who may fa...
The field of survival analysis has experienced tremendous growth during the latter half of the 20th ...
Competing events can preclude the event of interest from occurring in epidemiologic data and can be ...
The usefulness of time-to-event (survival) analysis has made it gain a wide applicability in statist...
“Competing Risks” refers to the study of the time to event where there is more than one type of fail...
The number needed to treat is a tool often used in clinical settings to illustrate the effect of a t...
Studies in cardiology often record the time to multiple disease events such as death, myocardial inf...
International audienceBACKGROUND: In medical research, one common competing risks situation is the s...
In many clinical studies the occurrence of different types of disease events over time is of interes...
Competing risks occur frequently in the analysis of survival data. A competing risk is an event whos...
Free to read Competing events are common in medical research. Ignoring them in the statistical analy...
In studies with survival or time-to-event outcomes, a competing risk is an event whose occurrence pr...
In many instances, a subject can experience both a nonterminal and terminal event where the terminal...
In assessing time to event endpoints, data are said to exhibit competing risks if subjects can fail ...
Competing events can preclude the event of interest from occurring in epidemiologic data and can be ...
Clinical trials and cohort studies that collect survival data frequently involve patients who may fa...
The field of survival analysis has experienced tremendous growth during the latter half of the 20th ...
Competing events can preclude the event of interest from occurring in epidemiologic data and can be ...
The usefulness of time-to-event (survival) analysis has made it gain a wide applicability in statist...
“Competing Risks” refers to the study of the time to event where there is more than one type of fail...
The number needed to treat is a tool often used in clinical settings to illustrate the effect of a t...
Studies in cardiology often record the time to multiple disease events such as death, myocardial inf...
International audienceBACKGROUND: In medical research, one common competing risks situation is the s...
In many clinical studies the occurrence of different types of disease events over time is of interes...
Competing risks occur frequently in the analysis of survival data. A competing risk is an event whos...
Free to read Competing events are common in medical research. Ignoring them in the statistical analy...
In studies with survival or time-to-event outcomes, a competing risk is an event whose occurrence pr...
In many instances, a subject can experience both a nonterminal and terminal event where the terminal...
In assessing time to event endpoints, data are said to exhibit competing risks if subjects can fail ...
Competing events can preclude the event of interest from occurring in epidemiologic data and can be ...
Clinical trials and cohort studies that collect survival data frequently involve patients who may fa...
The field of survival analysis has experienced tremendous growth during the latter half of the 20th ...