Frailty models power variance function with cure fraction and latent risk factors negative binomial

DOI10.1080/03610926.2016.1218029zbMath1380.62249OpenAlexW2521416982MaRDI QIDQ4598012

Vinicius F. Calsavara, Vera Lucia Tomazella, Agatha Rodrigues, Mário de Castro

Publication date: 15 December 2017

Published in: Communications in Statistics - Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1080/03610926.2016.1218029

zbMATH Keywords

parameter estimationmaximum likelihood estimationMonte Carlo simulationcompeting risksfrailty modelscure rate modelscancer recurrencepower variance function (PVF) distribution

Mathematics Subject Classification ID

Applications of statistics to biology and medical sciences; meta analysis (62P10) Reliability and life testing (62N05)

Related Items (5)

Zero-adjusted defective regression models for modeling lifetime data ⋮ Defective models induced by gamma frailty term for survival data with cured fraction ⋮ The Log-Normal zero-inflated cure regression model for labor time in an African obstetric population ⋮ Unnamed Item ⋮ The negative binomial beta prime regression model with cure rate: application with a melanoma dataset

This page was built for publication: Frailty models power variance function with cure fraction and latent risk factors negative binomial