Practicality of Some Variations of Ranked Set Sampling
Judgement ranking in ranked set sampling (RSS) and its variations depends on the ability of an observer to rank a set of objects according to the study variable without doing any actual measurement. In practice, and in some variations of RSS, it is hard to assign these ranks. In this paper, we discuss the practicality of ranking some extensions of RSS such as median RSS, double median RSS, and double RSS. The Hellinger distance is used as a measure of practicality. Although double median RSS is the most efficient approach among the RSS variations considered, it is shown in this paper that it is the least practical.
How to Cite
Copyright (c) 2020 Austrian Journal of Statistics
This work is licensed under a Creative Commons Attribution 3.0 International License.
The Austrian Journal of Statistics publish open access articles under the terms of the Creative Commons Attribution (CC BY) License.
The Creative Commons Attribution License (CC-BY) allows users to copy, distribute and transmit an article, adapt the article and make commercial use of the article. The CC BY license permits commercial and non-commercial re-use of an open access article, as long as the author is properly attributed.
Copyright on any research article published by the Austrian Journal of Statistics is retained by the author(s). Authors grant the Austrian Journal of Statistics a license to publish the article and identify itself as the original publisher. Authors also grant any third party the right to use the article freely as long as its original authors, citation details and publisher are identified.
Manuscripts should be unpublished and not be under consideration for publication elsewhere. By submitting an article, the author(s) certify that the article is their original work, that they have the right to submit the article for publication, and that they can grant the above license.