Ranked Set Sampling: Its Relevance and Impact on Statistical Inference. (31st December 2012)

• Record Type: Journal Article
• Authors: Wolfe, Douglas A.
• Other Names: Fagnola F. Academic Editor.; Lototsky S. Academic Editor.; Proppe C. Academic Editor.; Sacerdote L. Academic Editor.
• Is Part Of: ISRN probability and statistics. Volume 2012(2012)
• Publication Date: 2012-12-31
• Subjects: Probabilities -- Periodicals; Mathematical statistics -- Periodicals; Mathematical statistics; Probabilities; Electronic journals; Periodicals; 519
• DOI: 10.5402/2012/568385
• Languages: English
• ISSNs: 2090-4711

Abstract

Abstract : Ranked set sampling (RSS) is an approach to data collection and analysis that continues to stimulate substantial methodological research. It has spawned a number of related methodologies that are active research arenas as well, and it is finally beginning to find its way into significant applications beyond its initial agricultural-based birth in the seminal paper by McIntyre (1952). In this paper, we provide an introduction to the basic concepts underlying ranked set sampling, in general, with specific illustrations from the one- and two-sample settings. Emphasis is on the breadth of the ranked set sampling approach, with targeted discussion of the many options available to the researcher within the RSS paradigm. The paper also provides a thorough bibliography of the current state of the field and introduces the reader to some of the most promising new methodological extensions of the RSS approach to statistical data analysis.