Survival analyses with dependent covariates: A regression tree-base approach

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Boskabadi Mostafa; Doostparast Mahdi; SARMAD MAJID

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Journal: JOURNAL OF ALGORITHMS AND COMPUTATION Year:2020 | Volume:52 | Issue:1 Page(s): 105-129

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Title

Survival analyses with dependent covariates: A regression tree-base approach

Author(s)

Boskabadi Mostafa | Doostparast Mahdi | SARMAD MAJID | Issue Writer Certificate

Keywords

Survival tree

Cox proportional hazards model

Dependence

Copula function

Abstract

Cox proportional hazards models are the most common modelling framework to prediction and evaluation of co-variate e ects 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.

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Modeling and Identification of Factors Affecting the Existence of Complications Caused by Diabetes with Data Mining Methods

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APA: Copy

Boskabadi, Mostafa, Doostparast, Mahdi, & SARMAD, MAJID. (2020). Survival analyses with dependent covariates: A regression tree-base approach. JOURNAL OF ALGORITHMS AND COMPUTATION, 52(1), 105-129. SID. https://sid.ir/paper/354591/en

Vancouver: Copy

Boskabadi Mostafa, Doostparast Mahdi, SARMAD MAJID. Survival analyses with dependent covariates: A regression tree-base approach. JOURNAL OF ALGORITHMS AND COMPUTATION[Internet]. 2020;52(1):105-129. Available from: https://sid.ir/paper/354591/en

IEEE: Copy

Mostafa Boskabadi, Mahdi Doostparast, and MAJID SARMAD, “Survival analyses with dependent covariates: A regression tree-base approach,” JOURNAL OF ALGORITHMS AND COMPUTATION, vol. 52, no. 1, pp. 105–129, 2020, [Online]. Available: https://sid.ir/paper/354591/en

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