PUBLICATIONS

Here is a list of some recent publications of the project

L. Castro; M. Rueda; C. Sánchez-Cantalejo; R. Ferri; A. Cabrera. 2024.
Calibration and XGBoost reweighting to reduce coverage and non-response biases in overlapping panel surveys: Application to the Healthcare and Social Survey.
BMC Medical Research Methodology. 15 Feb 2024, 24(1):36 DOI.

Sergio Martínez; María D. Illescas; María del Mar Rueda. 2024.
Calibration estimation of distribution function based on multidimensional scaling auxiliary information.
Journal of Computational and Applied Mathematics. Elsevier. DOI.

J. Fernando Vera, C. Cecilia Sánchez Zuleta, María del Mar Rueda. 2023.
A unified approach based on multidimensional scaling for calibration estimation in survey sampling with qualitative auxiliary information.
Statistical Methods in Medical Research. DOI.

María del Mar Rueda. 2023.
Book review Silvia Biffignandi and Jelke Bethlehem. Handbook of Web Surveys, 2nd edition. 2021, Wiley, A look at non-probability surveys.
Journal of Official Statistics. 39-4, pp.591-595 DOI.

Sergio Martínez, María D. Illescas, María del Mar Rueda. 2023.
Distribution function estimation with calibration on principal components.
Journal of Computational and Applied Mathematics. 428-115189. DOI.

María del Mar Rueda, Beatriz Cobo, Jorge Rueda, Ramón Ferri, Luis Castro. 2024.
Kernel Weighting for blending probability and non-probability survey samples.
SORT-Statistics and Operations Research Transactions 2024 DOI.

Carmen Sánchez-Cantalejo Garrido, Daniela Yucumá Conde, María del Mar Rueda, Antonio Olry-de-Labry-Lima, Eva Martín-Ruiz, Camila Higueras-Callejón, Andrés Cabrera-León.
Scoping Review of the methodology of large health surveys conducted in Spain early on in the COVID-19 pandemic.
Frontiers in Public Health. 100. DOI.

A Cabrera-Léon, L Castro-Martín, M Rueda, C Sánchez-Cantalejo, R Ferri-García. 2023.
Reweighting in panel surveys: machine learning techniques for the Health Care and Social Survey.
European Journal of Public Health 2023-10-24 DOI.

María del Mar Rueda, Sara Pasadas-del-Amo, Beatriz Cobo Rodríguez, Luis Castro-Martín, Ramón Ferri-García 2022.
Enhancing estimation methods for integrating probability and nonprobability survey samples with machine-learning techniques. An application to a Survey on the impact of the COVID-19 pandemic in Spain.
Biometrical Journal. pp.1-19. DOI.

Mhairi Gibson, Eshetu Gurmu, Beatriz Cobo, M. Rueda, Isabel Scott. 2022.
Measuring hidden support for physical intimate partner violence: a list randomization experiment in South-Central Ethiopia.
Journal of Interpersonal Violence. 37, pp.7-8. DOI.

María del Mar Rueda, Sergio Martínez-Puertas, Luis Castro-Martín. 2022.
Methods to Counter Self-Selection Bias in Estimations of the Distribution Function and Quantiles.
Mathematics. 10-4726. DOI.

María del Mar Rueda; Sergio Martínez Puertas. 2022.
Reduction of optimal calibration dimension with a new optimal auxiliary vector for calibrated estimators of the distribution function.
Mathematical Methods in the Applied Sciences. 45(17), pp.10959-10981. DOI.

R. Ferri; M. Rueda. 2022.
Variable selection in Propensity Score Adjustment to mitigate selection bias in online surveys.
Statistical Papers. 63-6, pp.1829-1881. DOI.

Sergio Martínez; María del Mar Rueda; María Dolores Illescas. 2022.
Reduction of optimal calibration dimension with a new optimal auxiliary vector for calibrated estimators of the distribution function Mathematical
Methods in the Applied Sciences 2022-11-30 DOI.

L. Castro, M. Rueda, R. Ferri, C. Hernando. 2021.
On the use of gradient boosting methods to improve the estimation with data obtained with self-selection procedures.
Mathematics. MDPI. 9-23, pp.2991. DOI.

C. Sánchez-Cantalejo; A. Cabrera; (3/10) M. Rueda; et al; A. Daponte. 2021.
COVID-19 impact on the health and emotional wellbeing of the general population.
European Journal of Public Health. 12-sup. 3. DOI.

L. Castro, M. Rueda, R. Ferri. 2021.
Combining Statistical Matching and Propensity Score Adjustment for Inference from Non-Probability Surveys.
Journal of Computational and Applied Mathematics. 404, pp.113414. DOI.

R. Ferri, M. Rueda, L. Castro. 2021.
Evaluating Machine Learning methods for estimation in online surveys with superpopulation modeling.
Mathematics and Computers in Simulation. Elservier. 186, pp.19-28. DOI.

Ferri-García, Ramón; Beaumont, Jean-François; Bosa, Keven; Charlebois, Joanne; Chu, Kenneth. 2021.
Weight smoothing for nonprobability surveys.
TEST, 1-25. DOI.

Carmen Sánchez Cantalejo, M. Rueda, Marc Sáez, et al, Andrés Cabrera. 2021.
Impact of COVID-19 on the health of the general and more vulnerable population and its determinants: Health care and social survey-ESSOC, study protocol.
International Journal of Environmental Research and Public Health. 18-15, pp.8120. DOI.

B. Cobo, E. Castillo, F. López, M. Rueda. 2021.
Indirect questioning methods for sensitive survey questions: modelling criminal behaviours among a prison population.
PlosOne. 16-1, pp.e0245550. DOI.

M. Rueda, B. Cobo, P. F. Perri. 2021.
New estimation techniques for ordinal sensitive variables.
Mathematics and Computers in Simulation. 186, pp.62-70. DOI.

Sebastian Rinke, Sara Pasadas, Beatriz Cobo, M. Rueda. 2021.
No Magic Bullet: Estimating Anti-Immigrant Sentiment and Social Desirability Bias with the Item-Count.
Quality and Quantity. 55-6, pp.2139-2159. DOI.

M. Rueda, M.G. Ranalli, A. Arcos, D. Molina. 2021.
Population Empirical Likelihood Estimation in Dual Frame Surveys.
Statistical Papers. 62, pp.2473-2490. DOI.

M. Rueda, B. Cobo, A. Arcos. 2021.
Regression models in complex survey sampling for sensitive quantitative variables.
Mathematics. MDPi. 9-6, pp.609. DOI.

R. Ferri, M. Rueda, A. Cabrera. 2021.
Self-perceived health, life satisfaction and related factors among healthcare professionals and the general population: analysis of an online survey, with propensity score adjustment.
Mathematics. MDPI. 9-7, pp.791. DOI.

M. Rueda, S. Martínez, M. Illescas. 2021.
Treating nonresponse in the estimation of the distribution function.
Mathematics and Computers in Simulation. 186, pp.136-144. DOI.

R. Ferri, L. Castro, ,M. Rueda. 2020.
Estimating General Parameters from Non-Probability Surveys using Propensity Score Adjustment.
Mathematics. 8-11, pp.1-14. DOI.

I. Sánchez, M. Rueda, H. Mullo. 2020.
Estimation of Non-Linear Parameters with Data Collected Using Respondent-Driven Sampling.
Mathematics. 8-8, pp.1315. DOI.

L. Castro, M. Rueda, R. Ferri. 2020.
Inference from non-probability surveys with statistical matching and propensity score adjustment using modern prediction techniques.
Mathematics. MDPI. 8-6, pp.879. DOI.

B. Cobo, M. Rueda, F. López. 2020.
Measuring inappropriate sexual behaviour among university students: using the randomized response technique to enhance self-reporting.
Sexual Abuse: A Journal of Research and Treatment. SAGE journals. 32-3, pp.320-334. ISSN 1079-0632. DOI.

R. Ferri, M. Rueda. 2020.
Propensity score adjustment using machine learning classification algorithms to control selection bias in online surveys.
PLOS One. 15-4. DOI.

M. Rueda, R. Ferri, L. Castro. 2020.
The R package NonProbEst for estimation in non-probability surveys.
R journal. R project. 12-1, pp.405-417. PDF.

Mullo, H., Sánchez-Borrego, I., Pasadas-del-Amo, S. 2020
Respondent-Driven Sampling for Surveying Ethnic Minorities in Ecuador.
Sustainability 2020, 12, 9102. DOI.