RT Book, Section
SR 00
ID 10.1007/978-3-030-73249-3_3
A1 Casanova, Sandrine
A1 Leconte, Eve
T1 Nonparametric Model-Based Estimators for the Cumulative Distribution Function of a Right Censored Variable in a Small Area
YR 2021
FD 2021-06
SP 710
AB In survey analysis, the estimation of the cumulative distribution function (cdf) is of great interest as it facilitates the derivation of mean/median estimators for both populations and sub-populations (i.e. domains). We focus on small domains and consider the case where the response variable is right censored. Under this framework, we propose a nonparametric model-based estimator that extends the cdf estimator of Casanova (2012) to the censored case: it uses auxiliary information in the form of a continuous covariate and utilizes nonparametric quantile regression. We then employ simulations to compare the constructed estimator with the model-based cdf estimator of Casanova and Leconte (2015) and the Kaplan–Meier estimator (Kaplan and Meier 1958), both of which use only information contained within the domain: the quantile-based estimator performs better than the former two for very small domain sample sizes. Access times to the first job for young female graduates in the Occitania region are used to illustrate the new methodology.
A2 Daouia, Abdelaati
A2 Ruiz-Gazen, Anne
T2 Advances in Contemporary Statistics and Econometrics
PB Springer International Publishing
SN 978-3-030-73248-6
AV Published
LK https://publications.ut-capitole.fr/id/eprint/43702/
UL http://tse-fr.eu/pub/125828