Behavior of t-statistic in Multiple Hypothesis Testing Problem

碩士 === 國立交通大學 === 統計學研究所 === 97 === Microarray data has been studied widely, with thousands or even millions of test statistics ti's to be considered at the same time. These test statistics ti's are correlated or not regular distributed on multiple testing procedure. In this paper, we disc...

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Main Authors: Wang, Yi-Lun, 王怡倫
Other Authors: Hung, Hui-Nien
Format: Others
Language:en_US
Online Access:http://ndltd.ncl.edu.tw/handle/23043904325865465824
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spelling ndltd-TW-097NCTU53370072015-10-13T15:42:19Z http://ndltd.ncl.edu.tw/handle/23043904325865465824 Behavior of t-statistic in Multiple Hypothesis Testing Problem 多重假設檢定問題下t統計量的行為 Wang, Yi-Lun 王怡倫 碩士 國立交通大學 統計學研究所 97 Microarray data has been studied widely, with thousands or even millions of test statistics ti's to be considered at the same time. These test statistics ti's are correlated or not regular distributed on multiple testing procedure. In this paper, we discussed three possible reasons for the distribution of test statistics ti's differing from t-distribution. The three reasons are correlation between genes, correlation among microarrays, and various distribution assumptions. Then, we consider several models and conclude that correlation among microarrays and various distribution assumptions are most important effects which make the distribution of test statistics ti's differing from t-distribution. Key words: Multiple testing procedure, t-statistics, t-distribution. Hung, Hui-Nien 洪慧念 學位論文 ; thesis 24 en_US
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language en_US
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description 碩士 === 國立交通大學 === 統計學研究所 === 97 === Microarray data has been studied widely, with thousands or even millions of test statistics ti's to be considered at the same time. These test statistics ti's are correlated or not regular distributed on multiple testing procedure. In this paper, we discussed three possible reasons for the distribution of test statistics ti's differing from t-distribution. The three reasons are correlation between genes, correlation among microarrays, and various distribution assumptions. Then, we consider several models and conclude that correlation among microarrays and various distribution assumptions are most important effects which make the distribution of test statistics ti's differing from t-distribution. Key words: Multiple testing procedure, t-statistics, t-distribution.
author2 Hung, Hui-Nien
author_facet Hung, Hui-Nien
Wang, Yi-Lun
王怡倫
author Wang, Yi-Lun
王怡倫
spellingShingle Wang, Yi-Lun
王怡倫
Behavior of t-statistic in Multiple Hypothesis Testing Problem
author_sort Wang, Yi-Lun
title Behavior of t-statistic in Multiple Hypothesis Testing Problem
title_short Behavior of t-statistic in Multiple Hypothesis Testing Problem
title_full Behavior of t-statistic in Multiple Hypothesis Testing Problem
title_fullStr Behavior of t-statistic in Multiple Hypothesis Testing Problem
title_full_unstemmed Behavior of t-statistic in Multiple Hypothesis Testing Problem
title_sort behavior of t-statistic in multiple hypothesis testing problem
url http://ndltd.ncl.edu.tw/handle/23043904325865465824
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