The Bivariate Defective Gompertz Distribution Based on Clayton Copula with Applications to Medical Data release_h3fctbvoczhdxk42i4sp7uju2m

by Marcos Peres, Ricardo Puziol De Oliveira, Jorge Achcar, Edson Martinez

Published in Austrian Journal of Statistics by Austrian Statistical Society.

2022   Volume 51, p144-168

Abstract

In medical studies, it is common the presence of a fraction of patients who do not experience the event of interest. These patients are people who are not at risk of the event or are patients who were cured during the research. The proportion of immune or cured patients is known in the literature as cure rate. In general, the traditional existing lifetime statistical models are not appropriate to model data sets with cure rate, including bivariate lifetimes. In this paper, it is proposed a bivariate model based on a defective Gompertz distribution and also using a Clayton copula function to capture the possible dependence structure between the lifetimes. An extensive simulation study was carried out in order to evaluate the biases and the mean squared errors for the maximum likelihood estimators of the parameters associated to the proposed distribution. Some applications using medical data are presented to show the usefulness of the proposed model. Maximum likelihood and Bayesian methods were used to estimate the parameters of the model.
In application/xml+jats format

Archived Files and Locations

application/pdf  1.8 MB
file_nmnj4ja22redfki6fyq47tb62a
www.ajs.or.at (publisher)
web.archive.org (webarchive)
Read Archived PDF
Preserved and Accessible
Type  article-journal
Stage   published
Date   2022-01-25
Journal Metadata
Open Access Publication
In DOAJ
Not in Keepers Registry
ISSN-L:  1026-597X
Work Entity
access all versions, variants, and formats of this works (eg, pre-prints)
Catalog Record
Revision: fe1642f4-8c3f-491e-a0b6-98850fe62287
API URL: JSON