Estimation of Non-Linear Parameters with Data Collected Using Respondent-Driven Sampling Sánchez Borrego, Ismael Ramón Rueda García, María Del Mar Mullo, Héctor Respondent-driven sampling Regression Network dependence Respondent-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. 2020-11-09T13:05:52Z 2020-11-09T13:05:52Z 2020-08-07 info:eu-repo/semantics/article Sánchez-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] http://hdl.handle.net/10481/64153 10.3390/math8081315 eng http://creativecommons.org/licenses/by/3.0/es/ info:eu-repo/semantics/openAccess Atribución 3.0 España MDPI