Optimum Allocation of Stratified Random Samples Designed for Multiple Mean Estimates and Multiple Observed Variables

Abstract

With a fixed overall sampling cost, it is essential to achieve minimal error variance of the estimated population statistics in order to be maximally efficient. The error variance of a population mean estimate derived from a stratified random sample (StRS) may be minimized by determining the optimum allocation of observations to the strata. A variety of approaches currently exists to achieve this. Moreover, for obvious economic reasons, a survey's objective is generally more than the estimation of a single population mean of a single variable. That is, mean values restricted to various subsets of strata and mean values belonging to several observed variables are simultaneously estimated. Available optimization procedures, however, only partially address this issue. In this paper, a method

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