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Ranked Set Sampling Theory with Order Statistics Background

T. R. Dell and J. L. Clutter
Biometrics
Vol. 28, No. 2 (Jun., 1972), pp. 545-555
DOI: 10.2307/2556166
Stable URL: http://www.jstor.org/stable/2556166
Page Count: 11
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Ranked Set Sampling Theory with Order Statistics Background
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Abstract

Ranked set sampling employs judgment ordering to obtain an estimate of a population mean. The method is most useful when the measurement or quantification of an element is difficult but the elements of a set of given size are easily drawn and ranked with reasonable success by judgment. In each set all elements are ranked but only one is quantified. Sufficient sets are processed to yield a specified number of quantified elements and a mean for each rank. The average of these means is an unbiased estimate of the population mean regardless of errors in ranking. Precision relative to random sampling, with the same number of units quantified, depends upon properties of the population and success in ranking. In this paper the ranked set concept is reviewed with particular consideration of errors in judgment ordering.

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