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研究生:李凱平
研究生(外文):Kai-Ping Li
論文名稱:排序截切反轉常態法之探討
論文名稱(外文):Rank Truncated Inverse Normal Method for Combining P-values
指導教授:戴 政侯家鼎侯家鼎引用關係
指導教授(外文):John Jen TaiChia-Ding Hou
口試委員:林正祥李昭憲
口試委員(外文):Jheng-Siang LinJhao-Sian Li
口試日期:2013-07-04
學位類別:碩士
校院名稱:輔仁大學
系所名稱:統計資訊學系應用統計碩士班
學門:數學及統計學門
學類:統計學類
論文種類:學術論文
論文出版年:2013
畢業學年度:101
語文別:中文
論文頁數:89
中文關鍵詞:整合分析分位數合併法截切合併法L-統計量
外文關鍵詞:Meta-analysisQuantile combination methodsTruncated combination methodsL-statistic
相關次數:
  • 被引用被引用:2
  • 點閱點閱:264
  • 評分評分:
  • 下載下載:25
  • 收藏至我的研究室書目清單書目收藏:1
整合分析中的合併檢定法被廣泛應用於各個領域中,它可以整合不同的檢定資訊後,以得到一個更合理的檢定結果。在眾多合併檢定方法中,Fisher法是最常被廣泛使用且具有代表性的合併方法。在分量位合併法(quantile combination methods)的部分,因許多文獻提到反轉常態法(Inverse normal)在某些情況下其檢定力的表現會優於Fisher法;在截切合併法的部分,則已知排序截切相乘法(Rank truncated product method)會優於截切相乘法(Truncated product method)和Fisher法。基於以上結果,本研究考慮運用排序截切的概念,結合反轉常態法,建立出排序截切反轉常態法並推導出此新方法統計量的機率密度函數以及其百分位數。經由模擬比較發現,本研究所提出之新方法的檢定力表現,在某些情況下會優於Fisher法、反轉常態法和排序截切相乘法。
The methods for combining tests have been widely used in various meta-analysis. One of the commonly used method is the Fisher combination method, which combines the p-values of different tests in a nonlinear transformed manner. Basically, these are two types of combination methods, the quantile combination methods and truncated combination methods. Among the quantile combination methods, many studies have shown that the inverse normal method has better power performance than Fisher’s method. On the other hand, among the truncated combination methods, it is demonstrated that the rank truncated product method is superior to Fisher’s method and truncated product method. In the light of these results, this study aims to combine the rank truncated product method and the inverse normal method to establish a new method. In this thesis, we derive the exact probability density function and the percentiles of the method. The simulation results show that the proposed approach outperforms the established methods in many situations.
第壹章 緒論 1
第一節 研究背景 1
第二節 研究動機與目的 4
第三節 研究架構 4
第貳章 文獻探討 5
第一節 合併檢定統計量概述 5
第二節 常用的合併檢定統計量 6
第三節 排序統計量的線性組合統計量 14
第參章 研究方法 16
第二節 WRTIN分配之精確機率密度函數探討 17
第三節 RTIN近似分配及參數 25
第四節 RTIN之臨界值編表與討論 33
第肆章 模擬分析與討論 35
第一節 模擬資料的建構 35
第二節RTIN之型一誤差與最佳參數選擇 37
第三節 排序截切反轉常態法之模擬比較 42
第五章 結論與建議 70
第一節 研究結論 70
第二節 研究限制與建議 71
參考文獻 72
附錄一 排序截切反轉常態法精確臨界值表 77
附錄二 排序截切反轉常態法之常態近似參數與近似拒絕域臨界值表 80
附錄三 排序截切相乘法與排序截切反轉常態法之最佳截切個數 85

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仁大學應用統計研究所碩士論文,新北市。
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