TY - JOUR
T1 - Confidence intervals for the first crossing point of two hazard functions
AU - Cheng, M.-Y.
AU - Qiu, Peihua
AU - Tan, Xiaming
AU - Tu, Dongsheng
N1 - Ming-Yen Cheng’s research was supported in part by the National Science Council grant NSC97-2118-M-002-001-MY3 and the Mathematics Division of the National Center of Theoretical Sciences (Taipei Office). Peihua Qiu’s research was supported in part by an NSF grant of USA. The research of Xianming Tan and Dongsheng Tu was supported by grants from National Cancer Institute of Canada and Nature Sciences and Engineering Research Council of Canada.
PY - 2009/11/1
Y1 - 2009/11/1
N2 - The phenomenon of crossing hazard rates is common in clinical trials with time to event endpoints. Many methods have been proposed for testing equality of hazard functions against a crossing hazards alternative. However, there has been relatively few approaches available in the literature for point or interval estimation of the crossing time point. The problem of constructing confidence intervals for the first crossing time point of two hazard functions is considered in this paper. After reviewing a recent procedure based on Cox proportional hazard modeling with Box-Cox transformation of the time to event, a nonparametric procedure using the kernel smoothing estimate of the hazard ratio is proposed. The proposed procedure and the one based on Cox proportional hazard modeling with Box-Cox transformation of the time to event are both evaluated by Monte–Carlo simulations and applied to two clinical trial datasets.
AB - The phenomenon of crossing hazard rates is common in clinical trials with time to event endpoints. Many methods have been proposed for testing equality of hazard functions against a crossing hazards alternative. However, there has been relatively few approaches available in the literature for point or interval estimation of the crossing time point. The problem of constructing confidence intervals for the first crossing time point of two hazard functions is considered in this paper. After reviewing a recent procedure based on Cox proportional hazard modeling with Box-Cox transformation of the time to event, a nonparametric procedure using the kernel smoothing estimate of the hazard ratio is proposed. The proposed procedure and the one based on Cox proportional hazard modeling with Box-Cox transformation of the time to event are both evaluated by Monte–Carlo simulations and applied to two clinical trial datasets.
UR - http://www.scopus.com/inward/record.url?eid=2-s2.0-70450231691&partnerID=MN8TOARS
U2 - 10.1007/s10985-009-9132-6
DO - 10.1007/s10985-009-9132-6
M3 - Journal article
SN - 1380-7870
VL - 15
JO - Lifetime Data Analysis
JF - Lifetime Data Analysis
M1 - 441
ER -