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
作品名稱（其他語言）
著者 Jyh-Shyang Wu; Wen-Shuenn Deng
單位
出版者
著錄名稱、卷期、頁數 Journal of Nonparametric Statistics 29(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
ISSN 1048-5252; 1029-0311
期刊性質 國外
收錄於 SCI
產學合作
通訊作者 Wen-Shuenn Deng
審稿制度 是
國別 GBR
公開徵稿
出版型式 ,電子版
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