Testing the homogeneity of proportions for clustered binary data without knowing the correlation structure

Please use this identifier to cite or link to this item: https://ir.lib.ncu.edu.tw/handle/987654321/105918

Title:	Testing the homogeneity of proportions for clustered binary data without knowing the correlation structure
Authors:	鄒宗山;Tsou, Tsung-Shan;Liu, Hsiao-Yun
Contributors:	理學院統計研究所
Keywords:	Asymptotic properties;Bartlett's second identity;Binary data;binomial model;Cluster analysis;cluster binary data;Clusters;Comparative analysis;Correlation;Correlation analysis;Data analysis;Data processing;Homogeneity;Maximum likelihood method;model misspecification;score statistic;Simulation;Statistical tests;Studies
Date:	2015-01-01
Issue Date:	2026-04-23 13:00:57 (UTC+8)
Publisher:	Routledge;Abingdon: Taylor & Francis
Abstract:	摘要： A robust generalized score test for comparing groups of cluster binary data is proposed. This novel test is asymptotically valid for practically any underlying correlation configurations including the situation when correlation coefficients vary within or between clusters. This structure generally undermines the validity of the typical large sample properties of the method of maximum likelihood. Simulations and real data analysis are used to demonstrate the merit of this parametric robust method. Results show that our test is superior to two recently proposed test statistics advocated by other researchers. 出版者： Abingdon: Taylor & Francis 出版日期： 2015-08-03 出處： Journal of applied statistics, 2015-08, Vol.42 (8), p.1706-1715 資源來源： EBSCOhost Business Source Premier 版權： 2015 Taylor & Francis 2015 版權： Copyright Taylor & Francis Ltd. 2015 識別號： ISSN: 0266-4763 識別號： EISSN: 1360-0532 識別號： DOI: 10.1080/02664763.2015.1005062
Appears in Collections:	[Graduate Institute of Statistics] journal & Dissertation

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