title: Evaluation of the treatment time-lag effect for survival data.
abstract: Medical treatments often take a period of time to reveal their impact on subjects, which is the so-called time-lag effect in the literature. In the survival data analysis literature, most existing methods compare two treatments in the entire study period. In cases when there is a substantial time-lag effect, these methods would not be effective in detecting the difference between the two treatments, because the similarity between the treatments during the time-lag period would diminish their effectiveness. In this paper, we develop a novel modeling approach for estimating the time-lag period and for comparing the two treatments properly after the time-lag effect is accommodated. Theoretical arguments and numerical examples show that it is effective in practice.
authors.affiliation: Department of Mathematics and Statistics, Old Dominion University, Norfolk, VA, 23508, USA. kypark@odu.edu.
authors.forename: Kayoung
authors.initials: K
authors.lastname: Park
authors.affiliation: Department of Biostatistics, University of Florida, Gainesville, FL, 32611, USA.
authors.forename: Peihua
authors.initials: P
authors.lastname: Qiu
mesh_terms: D000465:Algorithms; D003627:Data Interpretation, Statistical; D006801:Humans; D016016:Proportional Hazards Models; D016019:Survival Analysis; D061665:Time-to-Treatment
keywords: Cox proportional hazards model; Crossing hazard rates; Lag effect; Survival analysis; Treatment comparison