On sample allocation for efficient domain estimation - ARCHIVED

Sample allocation issues are studied in the context of estimating sub-population (stratum or domain) means as well as the aggregate population mean under stratified simple random sampling. A non-linear programming method is used to obtain "optimal" sample allocation to strata that minimizes the total sample size subject to specified tolerances on the coefficient of variation of the estimators of strata means and the population mean. The resulting total sample size is then used to determine sample allocations for the methods of Costa, Satorra and Ventura (2004) based on compromise allocation and Longford (2006) based on specified "inferential priorities". In addition, we study sample allocation to strata when reliability requirements for domains, cutting across strata, are also specified. Performance of the three methods is studied using data from Statistics Canada's Monthly Retail Trade Survey (MRTS) of single establishments.