Cox proportional hazards models are the most common modelling framework to prediction and evaluation of covariate effects in time-to-event analyses. These models usually do not account the relationship among covariates which may have impacts on survival times. In this article, we introduce regression tree models for survival analyses by incorporating dependencies among covariates. Various properties of the proposed model are studied 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.

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