Rivera-Rodriguez, Claudia

Optimal sample allocation for regression parameters

Department of Statistics, University of Auckland

It is well known that the efficiency of the parameter to be estimated will depend largely on the sampling design, the information available in the population and what criteria is used for optimization. There is a number of reasons why investigators may want to stratify before a sample is collected. One of the reasons is that it can offer gains in efficiency (smaller variances) when the target variable behaves differently between strata. Another reason is that estimates for each strata may be required. In both cases, there is always a question that investigators want an answer for: What is the best (yields the smaller variance) sample size for each strata given that budget is available for a total sample of size \(n\)?.

The answer to this question depend on different aspects such as the target of estimation? (Regression parameters) and the stratifying variable. Most survey-sampling research has focused on the estimation of totals of variables (not regression parameters). In this project we evaluate the efficiency of different methods of allocation for regression parameters. This is done through simulations and an application to the CHIS Survey data.