@misc{10481/104746,
year = {2023},
url = {https://hdl.handle.net/10481/104746},
abstract = {In this paper we review some methods proposed in the literature for combining a nonprobability and a probability sample with the purpose of obtaining an estimator with a smaller bias and standard error than the estimators that can be obtained using only the probability sample. We propose a new methodology based on the kernel weighting method. We discuss the properties of the new estimator when there is only selection bias and when there are both coverage and selection biases. We perform an extensive simulation study to better understand the behaviour of the proposed estimator.},
organization = {This work is part of grant PID2019-106861RB-I00 funded by MCIN/ AEI/10.13039/50 1100011033, by grant PDC2022-133293-I00 funded by MCIN/AEI/10.13039/5011000 11033 and the European Union “NextGenerationEU”/PRTR”1 and the grant FEDER C-EXP-153-UGR23 funded by Consejer´ıa de Universidad, Investigaci´on e Innovaci´on and by ERDF Andalusia Program 2021-2027. The research was also partially supported from IMAG-Maria de Maeztu CEX2020-001105-M/AEI/10.13039/501100011033.},
publisher = {Inst Estadística Catalunya-Idescat},
keywords = {Kernel weighting},
keywords = {survey sampling},
keywords = {non-probability sample},
keywords = {coverage bias},
keywords = {selection bias},
title = {Kernel Weighting for blending probability and non-probability survey samples},
doi = {10.57645/20.8080.02.15},
author = {Rueda García, María Del Mar and Cobo Rodríguez, Beatriz and Rueda-Sánchez, Jorge Luis and Ferri García, Ramón and Castro Martín, Luis},
}