On the approximations of critical values and power comparisons of several combination test methods under the dependence assumption

碩士 === 輔仁大學 === 統計資訊學系應用統計碩士班 === 102 === Combining P-value from separate tests is a very useful approach for gathering information of significance, and these methods have been widely used in various aspects of application. Accordingly, comparing the power performances of different combination metho...

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Main Authors: Huang Fang Yi, 黃方意
Other Authors: John Jen Tai, Chia-Ding Hou
Format: Others
Language:zh-TW
Published: 2014
Online Access:http://ndltd.ncl.edu.tw/handle/28583660408837546265
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spelling ndltd-TW-102FJU005060122016-02-28T04:20:21Z http://ndltd.ncl.edu.tw/handle/28583660408837546265 On the approximations of critical values and power comparisons of several combination test methods under the dependence assumption 相依情境下常見合併方法之臨界點近似與檢定力比較 Huang Fang Yi 黃方意 碩士 輔仁大學 統計資訊學系應用統計碩士班 102 Combining P-value from separate tests is a very useful approach for gathering information of significance, and these methods have been widely used in various aspects of application. Accordingly, comparing the power performances of different combination methods for helping researchers in selection of a suitable method in a practical study turns out to be an important issue in this area. Through simulation, Loughin(2004) had systematically compared six well-known combination methods under the assumption that the separate tests are independent. However, there is no research that has been done on comparing these combination methods under the scenario that separate tests are dependent. In this thesis, the respective approximate formulas are proposed for the critical values of five well-known combination methods under the dependence scenario. A series of simulations are conducted to compare power performances of these methods. John Jen Tai, Chia-Ding Hou 戴 政 、侯家鼎 2014 學位論文 ; thesis 87 zh-TW
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language zh-TW
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description 碩士 === 輔仁大學 === 統計資訊學系應用統計碩士班 === 102 === Combining P-value from separate tests is a very useful approach for gathering information of significance, and these methods have been widely used in various aspects of application. Accordingly, comparing the power performances of different combination methods for helping researchers in selection of a suitable method in a practical study turns out to be an important issue in this area. Through simulation, Loughin(2004) had systematically compared six well-known combination methods under the assumption that the separate tests are independent. However, there is no research that has been done on comparing these combination methods under the scenario that separate tests are dependent. In this thesis, the respective approximate formulas are proposed for the critical values of five well-known combination methods under the dependence scenario. A series of simulations are conducted to compare power performances of these methods.
author2 John Jen Tai, Chia-Ding Hou
author_facet John Jen Tai, Chia-Ding Hou
Huang Fang Yi
黃方意
author Huang Fang Yi
黃方意
spellingShingle Huang Fang Yi
黃方意
On the approximations of critical values and power comparisons of several combination test methods under the dependence assumption
author_sort Huang Fang Yi
title On the approximations of critical values and power comparisons of several combination test methods under the dependence assumption
title_short On the approximations of critical values and power comparisons of several combination test methods under the dependence assumption
title_full On the approximations of critical values and power comparisons of several combination test methods under the dependence assumption
title_fullStr On the approximations of critical values and power comparisons of several combination test methods under the dependence assumption
title_full_unstemmed On the approximations of critical values and power comparisons of several combination test methods under the dependence assumption
title_sort on the approximations of critical values and power comparisons of several combination test methods under the dependence assumption
publishDate 2014
url http://ndltd.ncl.edu.tw/handle/28583660408837546265
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