Application of a General Family of Bivariate Distributions in Modelling Dependent Competing Risks Data with Associated Model Selection
Methodology
2022-06-22 v1 Applications
Abstract
In this article, a general family of bivariate distributions is used to model competing risks data with dependent factors. The general structure of competing risks data considered here includes ties. A comprehensive inferential framework for the proposed model is presented: maximum likelihood estimation, confidence interval construction, and model selection within the bivariate family of distributions for a given dependent competing risks data. The inferential methods are very convenient to implement. Through detailed simulations, the inferential methods are observed to provide quite reasonable results. Analysis of a real data from the Diabetic Retinopathy Study is carried out with the help of the proposed model as an illustrative example.
Keywords
Cite
@article{arxiv.2206.09138,
title = {Application of a General Family of Bivariate Distributions in Modelling Dependent Competing Risks Data with Associated Model Selection},
author = {Aakash Agrawal and Ayon Ganguly and Debanjan Mitra},
journal= {arXiv preprint arXiv:2206.09138},
year = {2022}
}