Cox model versus generalized logrank test for time–to–event data with ties
نویسنده
چکیده
The Cox proportional hazards model is the standard tool for relative risk estimation and inference for survival studies. The generalized logrank (GLR) approach (Mehrotra and Roth, 2001) has been proposed as a more efficient alternative to the Cox model when the number of subjects is small and there are no ties in the data. However, ties will result if continuous data are grouped by rounding to the nearest day, week, etc. This paper investigates the use of bootstrap techniques to improve the efficiency of relative risk estimators and the accuracy of confidence intervals within the GLR framework in the presence of ties. Results from a simulation study are used to compare the Efron ∗Corresponding author’s email address: [email protected]
منابع مشابه
Augmenting the logrank test in the design of clinical trials in which non-proportional hazards of the treatment effect may be anticipated.
BACKGROUND Most randomized controlled trials with a time-to-event outcome are designed assuming proportional hazards (PH) of the treatment effect. The sample size calculation is based on a logrank test. However, non-proportional hazards are increasingly common. At analysis, the estimated hazards ratio with a confidence interval is usually presented. The estimate is often obtained from a Cox PH ...
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