A revisit to contingency table and tests of independence: Bootstrap is preferred to chi-square approximations as well as fisher's exact test

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题名:	A revisit to contingency table and tests of independence: Bootstrap is preferred to chi-square approximations as well as fisher's exact test
作者:	Lin, Jyh-Jiuan;Chang, Ching-Hui;Pal, Nabendu
关键词:	Hypothesis testing;Level of a test;Power of a test;Size
日期:	2015-05-04
上传时间:	2016-01-06 11:02:00 (UTC+8)
出版者:	Taylor & Francis Inc.
摘要:	To test the mutual independence of two qualitative variables (or attributes), it is a common practice to follow the Chi-square tests (Pearson's as well as likelihood ratio test) based on data in the form of a contingency table. However, it should be noted that these popular Chi-square tests are asymptotic in nature and are useful when the cell frequencies are "not too small." In this article, we explore the accuracy of the Chi-square tests through an extensive simulation study and then propose their bootstrap versions that appear to work better than the asymptotic Chi-square tests. The bootstrap tests are useful even for small-cell frequencies as they maintain the nominal level quite accurately. Also, the proposed bootstrap tests are more convenient than the Fisher's exact test which is often criticized for being too conservative. Finally, all test methods are applied to a few real-life datasets for demonstration purposes.
關聯:	Journal of Biopharmaceutical Statistics 25(3), p.438-458
DOI:	10.1080/10543406.2014.920851
显示于类别:	[統計學系暨研究所] 期刊論文

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