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dc.contributor.authorSánchez Borrego, Ismael Ramón 
dc.contributor.authorRueda García, María Del Mar 
dc.contributor.authorMullo, Héctor
dc.identifier.citationSánchez-Borrego, I.; Rueda, M.M.; Mullo, H. Estimation of Non-Linear Parameters with Data Collected Using Respondent-Driven Sampling. Mathematics 2020, 8, 1315. [doi:10.3390/math8081315]es_ES
dc.description.abstractRespondent-driven sampling (RDS) is a snowball-type sampling method used to survey hidden populations, that is, those that lack a sampling frame. In this work, we consider the problem of regression modeling and association for continuous RDS data. We propose a new sample weight method for estimating non-linear parameters such as the covariance and the correlation coefficient. We also estimate the variances of the proposed estimators. As an illustration, we performed a simulation study and an application to an ethnic example. The proposed estimators are consistent and asymptotically unbiased. We discuss the applicability of the method as well as future research.es_ES
dc.description.sponsorshipMinisterio de Economia, Industria y Competitividad, Spain MTM2015-63609-Res_ES
dc.rightsAtribución 3.0 España*
dc.subjectRespondent-driven samplinges_ES
dc.subjectNetwork dependencees_ES
dc.titleEstimation of Non-Linear Parameters with Data Collected Using Respondent-Driven Samplinges_ES

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Atribución 3.0 España
Except where otherwise noted, this item's license is described as Atribución 3.0 España