Adaptive cluster sampling, a quasi Bayesian approach
Articles and reports: 12-001-X202400200014Description: Adaptive cluster sampling designs were proposed as a method that could be used when sampling rare populations whose units tend to appear in clusters. The resulting estimator is not based on any model assumptions and is design unbiased. It can have smaller variance than the standard estimator which does not incorporate the fact that one is dealing with a rare population. Here we will demonstrate that, when adaptive cluster sampling is appropriate, its estimator does not take into account all the available information in the design. We present a quasi Bayesian approach which incorporates the information which is now ignored. We will see that the resulting estimator is a significant improvement over the current methods. Issue Number: 2024002Author(s): Meeden, Glen; Qureshi, Muhammad NoumanMain Product:Survey Methodology
