Una revisión de la metodología de estimación a través de muestreo por cadenas referenciales para las proporciones de una población oculta (2010)
This article reviews some of the most important results about a new method of sampling and estimation for populations where there is no sampling frame, this is known as Respondent-Driven Sampling (RDS). A theoretical analysis based on Markov chains shows that this method reduces the bias generally associated with chain-reference samples; in addition the method produces asymptotically unbiased estimators. We demonstrated the potential of the method through an empirical simulation.