Missing link survival analysis with applications to available pandemic data

Autor:	María Luz Gámiz, Enno Mammen, María Dolores Martínez-Miranda, Jens Perch Nielsen
Jazyk:	angličtina
Rok vydání:	2021
Předmět:	Statistics and Probability Double one-sided cross-validation Local linear estimation Applied Mathematics Missing data HA BF HN Article Computational Mathematics Computational Theory and Mathematics RA0421 QR180 QA Hazard
Zdroj:	Computational Statistics & Data Analysis
ISSN:	1872-7352 0167-9473
Popis:	It is shown how to overcome a new missing data problem in survival analysis. Iterative nonparametric techniques are utilized and the missing data information is both estimated and used for further estimation in each iterative step. Theory is developed and a good finite sample performance is illustrated by simulations. The main motivation is an application to French data on the temporal development of the number of hospitalized Covid-19 patients.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e8f738749d3deeb84deb167e4c1c2227 http://europepmc.org/articles/PMC8666881 Zobrazit plný text záznamu Full Text from ScienceDirect