@misc{10481/104745,
year = {2025},
url = {https://hdl.handle.net/10481/104745},
abstract = {collecting detailed data from individuals. Non-probability sampling is a relatively
inexpensive data source, although they require special treatment because the estimate
may suffer from sample selection bias. In this paper, we consider methods
for integrating a non-representative volunteer sample into a probability survey. We
investigate several approaches to correcting non-probability sample selection bias
in the estimation of the distribution function. We combine the estimators of the
distribution function that correct the selection bias with the design unbiased estimators
based on the probability sample. Our methodology for combining the voluntary
and probability samples can be applied to other non-linear parameters. Empirical
evidence of the improvements offered by the proposed methodology is provided in
simulation settings.},
organization = {The research was partially supported by MCIN/AEI /10.13039/501100011033,
PDC2022-133293-I00, Spain, Strategic Action in Health (DTS23/00032, Spain) and from IMAG-María
de Maeztu CEX2020-001105-M/AEI/10.13039/501100011033.},
publisher = {Springer Nature},
keywords = {Non-probability samples},
keywords = {Data integration},
keywords = {Survey sampling},
keywords = {Simulation},
title = {Estimation of the distribution function and quantiles through data integration},
doi = {https://doi.org/10.1007/s00362-025-01727-5},
author = {Cobo Rodríguez, Beatriz and Martínez, Sergio and Rueda García, María del Mar},
}