A nonparametric procedure for testing partially ranked data
學年 105
學期 2
出版(發表)日期 2017-03-20
作品名稱 A nonparametric procedure for testing partially ranked data
著者 Jyh-Shyang Wu and Wen-Shuenn Deng
著錄名稱、卷期、頁數 Journal of Nonparametric Statistics, vol.29, no.2, p.213~230
摘要 In consumer preference studies, it is common to seek a complete ranking of a variety of, say N, alternatives or treatments. Unfortunately, as N increases, it becomes progressively more confusing and undesirable for respondents to rank all N alternatives simultaneously. Moreover, the investigators may only be interested in consumers’ top few choices. Therefore, it is desirable to accommodate the setting where each survey respondent ranks only her/his most preferred k (k < N) alternatives. In this paper, we propose a simple procedure to test the independence of N alternatives and the top-k ranks, such that the value of k can be predetermined before securing a set of partially ranked data or be at the discretion of the investigator in the presence of complete ranking data. The asymptotic distribution of the proposed test under root-n local alternatives is established. We demonstrate our procedure with two real data sets.
關鍵字 Anderson’s test;partially ranked data;chi-square test;imposed rank;contingency table;U-statistics;root-n local alternatives
語言 en_US
期刊性質 國外
收錄於 SCI
國別 USA
出版型式 ,電子版,紙本

機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/111883 )