Estimation in a competing risks proportional hazards model under length-biased sampling with censoring View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2014-04

AUTHORS

Jean-Yves Dauxois, Agathe Guilloux, Syed N. U. A. Kirmani

ABSTRACT

What population does the sample represent? The answer to this question is of crucial importance when estimating a survivor function in duration studies. As is well-known, in a stationary population, survival data obtained from a cross-sectional sample taken from the population at time t(0) represents not the target density f (t) but its length-biased version proportional to t f (t), for t > 0. The problem of estimating survivor function from such length-biased samples becomes more complex, and interesting, in presence of competing risks and censoring. This paper lays out a sampling scheme related to a mixed Poisson process and develops nonparametric estimators of the survivor function of the target population assuming that the two independent competing risks have proportional hazards. Two cases are considered: with and without independent censoring before length biased sampling. In each case, the weak convergence of the process generated by the proposed estimator is proved. A well-known study of the duration in power for political leaders is used to illustrate our results. Finally, a simulation study is carried out in order to assess the finite sample behaviour of our estimators. More... »

PAGES

276-302

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/s10985-013-9248-6

DOI

http://dx.doi.org/10.1007/s10985-013-9248-6

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1005746761

PUBMED

https://www.ncbi.nlm.nih.gov/pubmed/23456312


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