A new technique for handling non-probability samples based on model-assisted kernel weighting

Beatriz Cobo, Jorge Luis Rueda-Sánchez, Ramón Ferri-García and María del Mar Rueda

Mathematics and Computers in Simulation (MATCOM), 2025, vol. 227, issue C, 272-281

Abstract: Surveys are going through massive changes, and the most important innovation is the use of non-probability samples. Non-probability samples are increasingly used for their low research costs and the speed of the attainment of results, but these surveys are expected to have strong selection bias caused by several mechanisms that can eventually lead to unreliable estimates of the population parameters of interest. Thus, the classical methods of statistical inference do not apply because the probabilities of inclusion in the sample for individual members of the population are not known. Therefore, in the last few decades, new possibilities of inference from non-probability sources have appeared.

Keywords: Model-assisted kernel; Kernel weighting; Employment; Confinement period; COVID-19 (search for similar items in EconPapers)
Date: 2025
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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:227:y:2025:i:c:p:272-281

DOI: 10.1016/j.matcom.2024.08.009

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