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Ranked set sampling for ordered categorical variables

โœ Scribed by Haiying Chen; Elizabeth A. Stasny; Douglas A. Wolfe

Publisher
John Wiley and Sons
Year
2008
Tongue
French
Weight
806 KB
Volume
36
Category
Article
ISSN
0319-5724

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โœฆ Synopsis

Abstract

The authors show how ranked set sampling, both balanced and unbalanced, can be extended to ordered categorical variables with the goal of estimating the probabilities of all categories. They use ordinal logistic regression to aid in the ranking of the ordinal variable of interest. They also propose an optimal allocation scheme and methods for implementing it under either perfect or imperfect rankings. Results from a simulation study using data from the third National Health and Nutrition Examination Survey indicate that the use of ordinal logistic regression in ranking leads to substantial gains in precision for estimation of cell probabilities.

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