Modeling Data With Semicompeting Risks: An Application to Chronic Kidney Disease in Colombia

Autor:	Maria Isabel Munera, Elizabeth González Patiño, Gisela Tunes
Rok vydání:	2019
Předmět:	Statistics and Probability Computer science Bivariate analysis medicine.disease ANÁLISE DE SOBREVIVÊNCIA Data modeling Data set Survival function Terminal and nonterminal symbols Econometrics medicine Shared frailty Event (probability theory) Kidney disease
Zdroj:	Repositório Institucional da USP (Biblioteca Digital da Produção Intelectual) Universidade de São Paulo (USP) instacron:USP
ISSN:	2389-8976 0120-1751
DOI:	10.15446/rce.v42n1.68572
Popis:	In this paper, the structure of semicompeting risks data, dened by Fine, Jiang & Chappell (2001), is studied. Two events are of interest: a nonterminal and a terminal event, the last one, can censor the non-terminal event, but not vice versa. Due to the possible dependence between the times until the occurrence of such events, two approaches are evaluated: modelling the bivariate survival function through Archimedean copulas and a shared frailty model. A simulation is conducted to examine its performance and both approaches are applied to a real data set of patients with chronic kidney disease (CKD).
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::eb688d20f6f929f1794b398ef5e3d79e https://doi.org/10.15446/rce.v42n1.68572 Zobrazit plný text záznamu Plný text ve formátu PDF