MUESTREO DE RESPUESTA ALEATORIZADAS CON PROBABILIDADES DESIGUALES: EL ESTIMADOR DE RAO-HARTLEY-COCHRAN.

The technique of Randomized Response has been introduced to reduce the risk of evasive answer or no-response in survey samplings of sensitive issues to estimate the total of individuals with that sensitive characteristic. We also know that highly efficient strategies of estimation require strong auxiliary information. Hence, in this article we obtain and compare two estimators: The Rao-Hartley-Cochran (RHC) estimator with Warner's model and the RHC estimator with Greenberg's model, both in a finite population setting. We will show via simulation that ŧA1,RHC,π the RHC π-estimator in Warner's model is less efficient than ŧA1,RHC,π, the RHC π-estimator in Greenberg's model. [ABSTRACT FROM AUTHOR]