Path consistent model selection in additive risk model via Lasso

Abstract

As a flexible alternative to the Cox model, the additive risk model assumes that the hazard function is the sum of the baseline hazard and a regression function of covariates. For right censored survival data when variable selection is needed along with model estimation, we propose a path consistent model selector using a modified Lasso approach, under the additive risk model assumption. We show that the proposed estimator possesses the oracle variable selection and estimation property. Applications of the proposed approach to three right censored survival data sets show that the proposed modified Lasso yields parsimonious models with satisfactory estimation and prediction results.