Estimation of Non-Linear Parameters with Data Collected Using Respondent-Driven Sampling
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Respondent-driven samplingRegressionNetwork dependence
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]
SponsorshipMinisterio de Economia, Industria y Competitividad, Spain MTM2015-63609-R
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.