title: Incorporating time-dependent covariates in survival analysis using the LVAR method.
abstract: In survival analysis, use of the Cox proportional hazards model requires knowledge of all covariates under consideration at every failure time. Since failure times rarely coincide with observation times, time-dependent covariates (covariates that vary over time) need to be inferred from the observed values. In this paper, we introduce the last value auto-regressed (LVAR) estimation method and compare it to several other established estimation approaches via a simulation study. The comparison shows that under several time-dependent covariate processes this method results in a smaller mean square error when considering the time-dependent covariate effect.
authors.affiliation: Department of Statistics, Purdue University, West Lafayette, IN 47907, USA. ylliu@stat.purdue.edu
authors.forename: Yali
authors.initials: Y
authors.lastname: Liu
authors.forename: Bruce A
authors.initials: BA
authors.lastname: Craig
mesh_terms: D003198:Computer Simulation; D006801:Humans; D016013:Likelihood Functions; D016016:Proportional Hazards Models; D016019:Survival Analysis