Hazard estimation with censoring and measurement error: application to length of pregnancy

Fabienne Comte (), Adeline Samson and Julien J. Stirnemann
Additional contact information
Fabienne Comte: University Paris Descartes, Sorbonne Paris Cité
Adeline Samson: Univ Grenoble-Alpes
Julien J. Stirnemann: University Paris Descartes

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research, 2018, vol. 27, issue 2, No 5, 338-359

Abstract: Abstract Estimation of the physiological length of pregnancy is a challenging problem since both the time origin of the pregnancy and the time of onset of labor are partly observed. The time to spontaneous labor is indeed right-censored, and the time of fertilization is only known up to an error. Therefore, data are subject to both censoring and measurement errors. We focus on the case where the measurement errors affect both the variable of interest and the censoring variable, which is the case of the timing of spontaneous delivery among pregnant women. We propose an estimation strategy to estimate the hazard rate of the underlying variable of interest. We explain the model and this strategy and provide $$L^2$$ L 2 -risk bound for the data driven resulting estimator. We also derive estimators of the survival function and the density. Simulations illustrate the performances of the estimator. Lastly, the method is applied to an original real data set of length of pregnancy to estimate rates of previable births, severe preterm births and prolonged pregnancy and the influence of the cervical length of the first semester.

Keywords: Censored data; Measurement error; Survival function estimation; Hazard rate function estimation; Nonparametric methods; Deconvolution; Length of pregnancy; 62G07; 62N01 (search for similar items in EconPapers)
Date: 2018
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s11749-017-0548-0 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:testjl:v:27:y:2018:i:2:d:10.1007_s11749-017-0548-0

Ordering information: This journal article can be ordered from
http://www.springer. ... cs/journal/11749/PS2

DOI: 10.1007/s11749-017-0548-0

Access Statistics for this article

TEST: An Official Journal of the Spanish Society of Statistics and Operations Research is currently edited by Alfonso Gordaliza and Ana F. Militino

More articles in TEST: An Official Journal of the Spanish Society of Statistics and Operations Research from Springer, Sociedad de Estadística e Investigación Operativa
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().