Estimation of the distribution function and quantiles through data integration Cobo Rodríguez, Beatriz Martínez, Sergio Rueda García, María del Mar Non-probability samples Data integration Survey sampling Simulation 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. 2025-06-23T07:19:27Z 2025-06-23T07:19:27Z 2025 journal article Cobo, B., Martínez, S. & Rueda, M. Estimation of the distribution function and quantiles through data integration. Stat Papers 66, 111 (2025). https://doi.org/10.1007/s00362-025-01727-5 https://hdl.handle.net/10481/104745 https://doi.org/10.1007/s00362-025-01727-5 eng http://creativecommons.org/licenses/by-nc-nd/4.0/ open access Attribution-NonCommercial-NoDerivatives 4.0 Internacional Springer Nature