Factor copula models for right-censored clustered survival data

Eleanderson Campos (), Roel Braekers, Devanil J. Souza and Lucas M. Chaves
Additional contact information
Eleanderson Campos: Federal University of Lavras
Roel Braekers: Universiteit Hasselt
Devanil J. Souza: Federal University of Lavras
Lucas M. Chaves: Federal University of Lavras

Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data, 2021, vol. 27, issue 3, No 8, 499-535

Abstract: Abstract In this article we extend the factor copula model to deal with right-censored event time data grouped in clusters. The new methodology allows for clusters to have variable sizes ranging from small to large and intracluster dependence to be flexibly modeled by any parametric family of bivariate copulas, thus encompassing a wide range of dependence structures. Incorporation of covariates (possibly time dependent) in the margins is also supported. Three estimation procedures are proposed: both one- and two-stage parametric and a two-stage semiparametric method where marginal survival functions are estimated by using a Cox proportional hazards model. We prove that the estimators are consistent and asymptotically normally distributed, and assess their finite sample behavior with simulation studies. Furthermore, we illustrate the proposed methods on a data set containing the time to first insemination after calving in dairy cattle clustered in herds of different sizes.

Keywords: Clustered survival data; Factor copula models; Intracluster dependence; Multivariate survival data; Varying cluster size (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10985-021-09525-5 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:lifeda:v:27:y:2021:i:3:d:10.1007_s10985-021-09525-5

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10985

DOI: 10.1007/s10985-021-09525-5

Access Statistics for this article

Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data is currently edited by Mei-Ling Ting Lee

More articles in Lifetime Data Analysis: An International Journal Devoted to Statistical Methods and Applications for Time-to-Event Data from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().