An expectation-conditional maximization-based Weibull-Gompertz mixture model for analyzing competing-risks data: Using post-transplant malignancy data

An expectation-conditional maximization-based Weibull-Gompertz mixture model for analyzing competing-risks data: Using post-transplant malignancy data

The aim of this study is to introduce a parametric mixture model to analysis the competing-risks data with two types of failure. In mixture context, ith type of failure is ith component. The baseline failure time for the first and second types of failure are modeled as proportional hazard models acc...

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Bibliographic Details
Main Authors: Mahmood Salesi, Abbas Rahimi-Foroushani, Jamile Mohammadi, Zohreh Rostami, Ali Reza Mehrazmay, Behzad Einollahi, Ali Reza Karambaksh, Saeed Asgharian, Mohammad Reza Eshraghian
Format: Article
Language:English
Published: Tehran University of Medical Sciences 2016-06-01
Series:Journal of Biostatistics and Epidemiology
Subjects:
mixture models
competing risks
expectation-conditional maximization algorithm
post-transplant malignancy
Online Access:https://jbe.tums.ac.ir/index.php/jbe/article/view/43

Internet

https://jbe.tums.ac.ir/index.php/jbe/article/view/43

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