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http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/54803
Title: | 錯誤發現率控制之模糊置換法 A Fuzzy Permutation Method for False Discovery Rate Control |
Authors: | Ya-Hui Yang 楊雅惠 |
Advisor: | 李文宗 |
Keyword: | 錯誤發現率,多重比較,隨機p值,置換法,蒙地卡羅模擬, false discovery rate,multiple comparisons,randomized p-values,permutation,Monte-Carlo simulation, |
Publication Year : | 2015 |
Degree: | 碩士 |
Abstract: | 生物醫學研究者進行研究時,經常會遇到大p小n的情境—個案數很少,但測量變數卻很多。我們提出模糊置換法,以解決小樣本情況下的多重檢定問題。此方法引進模糊量至標準置換法中產生隨機p值,而後轉換成q值以控制錯誤發現率。蒙地卡羅模擬顯示,我們的方法在資料是常態或非常態的情況下,都有良好的統計性質。我們分析一筆實際資料,作為範例。大p小n的情境下,我們推薦使用本研究提出的模糊置換法。 Biomedical researchers often encounter the large-p-small-n situations—a great number of variables are measured/recorded for only a few subjects. The authors propose a fuzzy permutation method to address the multiple testing problem for small sample size studies. The method introduces fuzziness into standard permutation analysis to produce randomized p-values, which are then converted into q-values for false discovery rate controls. Monte-Carlo simulations show that the proposed method has desirable statistical properties when the study variables are normally or non-normally distributed. A real dataset is analyzed to illustrate its use. The proposed fuzzy permutation method is recommended for use in the large-p-small-n settings. |
URI: | http://tdr.lib.ntu.edu.tw/jspui/handle/123456789/54803 |
Fulltext Rights: | 有償授權 |
Appears in Collections: | 流行病學與預防醫學研究所 |
Files in This Item:
File | Size | Format | |
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ntu-104-1.pdf Restricted Access | 320.23 kB | Adobe PDF |
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