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arXiv · 2206.09138

Application of a General Family of Bivariate Distributions in Modelling Dependent Competing Risks Data with Associated Model Selection

Aakash Agrawal·Ayon Ganguly·Debanjan Mitra
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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.

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Aakash Agrawal, Ayon Ganguly, Debanjan Mitra. 2022-06-18. Application of a General Family of Bivariate Distributions in Modelling Dependent Competing Risks Data with Associated Model Selection. https://arxiv.org/abs/2206.09138

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