A0833
Title: Variable selection for mixture and promotion time cure rate models
Authors: Abdullah Masud - Indiana University School of Medicine (United States)
Wanzhu Tu - Indiana University School of Medicine (United States)
Zhangsheng Yu - Shanghai Jiao Tong University (China) [presenting]
Abstract: Failure-time data with cured patients are common in clinical studies. Data from these studies are typically analyzed with cure rate models. Variable selection methods have not been well developed for cure rate models. We propose two Least Absolute Shrinkage and Selection Operators (LASSO) based methods, for variable selection in mixture and promotion time cure models with parametric or nonparametric baseline hazards. We conduct an extensive simulation study to assess the operating characteristics of the proposed methods. We illustrate the use of the methods using data from a study of childhood wheezing.
