2007•Communications in Statistics - Simulation and ComputationRequires access

Comparison of Efficiency of Stratified and Unequal Probability Sampling

Marcin Kozak, Andrzej Zieliński

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Abstract

In this article, a choice of the optimum sampling design to study a finite population is studied. Three sampling schemes are compared, viz., Sunter's procedure of unequal probability sampling, stratified sampling under optimum stratification, and simple random sampling without replacement. The comparison is made against a background of various correlation between stratification and survey variables and various variability in the variables. Under weak correlation and large variability, stratification appeared to be more efficient than Sunter's procedure. Under strong correlation and/or low variability in the variables, the latter procedure was the most efficient. Simple random sampling was usually the least efficient.

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What this paper is about

In this article, a choice of the optimum sampling design to study a finite population is studied. Three sampling schemes are compared, viz., Sunter's procedure of unequal probability sampling, stratified sampling under optimum stratification, and simple random sampling without replacement. The comparison is made against a background of various correlation between stratification and survey variables and various variability in the variables. Under weak correlation and large variability, stratification appeared to be more efficient than Sunter's procedure. Under strong correlation and/or low variability in the variables, the latter procedure was the most efficient. Simple random sampling was usually the least efficient.

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Available abstract

In this article, a choice of the optimum sampling design to study a finite population is studied. Three sampling schemes are compared, viz., Sunter's procedure of unequal probability sampling, stratified sampling under optimum stratification, and simple random sampling without replacement. The comparison is made against a background of various correlation between stratification and survey variables and various variability in the variables. Under weak correlation and large variability, stratification appeared to be more efficient than Sunter's procedure. Under strong correlation and/or low variability in the variables, the latter procedure was the most efficient. Simple random sampling was usually the least efficient.

Key concepts: Stratified sampling, Simple random sample, Statistics, Sampling (signal processing), Sampling design, Stratification (seeds), Mathematics, Poisson sampling

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