Stratified samples are commonly used when supplementary information is available to help with sample design. The precision of a stratified design is influenced by how the sample elements are allocated to strata. Neyman allocation is a method used to allocate sample to strata based on the strata variances and similar sampling costs in the strata. A Neyman allocation scheme provides the most precision for estimating a population mean given a fixed total sample size.
For stratified random sampling, the population is divided into H mutually exclusive strata. In each stratum, a simple random sample is drawn without replacement. Neyman allocation assigns sample units within each stratum proportional to the product of the population stratum size (Nh) and the within-stratum standard deviation (Sh), so that minimum variance ...
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