title: Comparison of multiple hazard rate functions.
abstract: Many robust tests have been proposed in the literature to compare two hazard rate functions, however, very few of them can be used in cases when there are multiple hazard rate functions to be compared. In this article, we propose an approach for detecting the difference among multiple hazard rate functions. Through a simulation study and a real-data application, we show that the new method is robust and powerful in many situations, compared with some commonly used tests.
authors.affiliation: Department of Epidemiology and Biostatistics, School of Public Health, Indiana University Bloomington, 1025 E. 7th street, Bloomington, Indiana, 47405, U.S.A.
authors.forename: Zhongxue
authors.initials: Z
authors.lastname: Chen
authors.affiliation: Department of Epidemiology and Biostatistics, College of Public Health, University of Georgia, Athens, Georgia 30602, U.S.A.
authors.forename: Hanwen
authors.initials: H
authors.lastname: Huang
authors.affiliation: Department of Biostatistics, College of Public Health & Health Professions and College of Medicine, University of Florida, Gainesville, Florida 32611, U.S.A.
authors.forename: Peihua
authors.initials: P
authors.lastname: Qiu
mesh_terms: D000465:Algorithms; D006801:Humans; D008137:Longitudinal Studies; D016016:Proportional Hazards Models; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D016019:Survival Analysis
keywords: Asymptotically independent; Counting process; Crossing; Survival data