Title of article :
Survival analyses with dependent covariates: A regression tree-base approach
Author/Authors :
Boskabadi, Mostafa Department of Statistics - Ferdowsi University of Mashhad, Khorasan Razavi , Doostparast, Mahdi Department of Statistics - Ferdowsi University of Mashhad, Khorasan Razavi , Sarmad, Majid Department of Statistics - Ferdowsi University of Mashhad, Khorasan Razavi
Abstract :
Cox proportional hazards models are the most common
modelling framework to prediction and evaluation of co-
variate eects in time-to-event analyses. These models
usually do not account the relationship among covari-
ates which may have impacts on survival times. In this
article, we introduce regression tree models for survival
analyses by incorporating dependencies among covari-
ates. Various properties of the proposed model are stud-
ied in details. To assess the accuracy of the proposed
model, a Monte{Carlo simulation study is conducted.
A real data set from assay of serum free light chain is
also analysed to illustrate advantages of the proposed
method in medical investigations.
Keywords :
Survival tree , Cox proportional hazards model , Dependence , Copula function
Journal title :
Journal of Algorithms and Computation