A New Weighted Combination Procedure

碩士 === 輔仁大學 === 統計資訊學系應用統計碩士班 === 100 === P-value combination procedures were proved to be very powerful in integrating results from multiple individual studies, especially when detail information is not available except p-values and sample size. Fisher method and inverse normal method are the two m...

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Main Authors: Yang, Ti-Sung, 楊廸雄
Other Authors: Hou, Chia-Ding
Format: Others
Language:zh-TW
Published: 2012
Online Access:http://ndltd.ncl.edu.tw/handle/61387979984578930138
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spelling ndltd-TW-100FJU005060292015-10-13T21:01:52Z http://ndltd.ncl.edu.tw/handle/61387979984578930138 A New Weighted Combination Procedure 一種新的加權檢定合併方法之探討 Yang, Ti-Sung 楊廸雄 碩士 輔仁大學 統計資訊學系應用統計碩士班 100 P-value combination procedures were proved to be very powerful in integrating results from multiple individual studies, especially when detail information is not available except p-values and sample size. Fisher method and inverse normal method are the two most commonly used methods for combining p-values. Many studies indicated that when the sensitivities of the individual studies are different, power of combination method can be improved by choosing weights for p-values appropriately. In this study, a new combination method “weighted Lancaster method” was proposed by incorporating weights into the statistic of Lancaster method, and an alternative approximation for the distribution of the combined statistic without the condition that combined p-values should be independent is derived. Through simulation studies, we show that the approximation proposed for the distribution of the statistic of weighted Lancaster method works quite well and power of weighted Lancaster method is superior to weighted inverse normal method and Lancaster method under most situations studied whether combined p-values are independent or not. Hou, Chia-Ding 侯家鼎 2012 學位論文 ; thesis 119 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 === 100 === P-value combination procedures were proved to be very powerful in integrating results from multiple individual studies, especially when detail information is not available except p-values and sample size. Fisher method and inverse normal method are the two most commonly used methods for combining p-values. Many studies indicated that when the sensitivities of the individual studies are different, power of combination method can be improved by choosing weights for p-values appropriately. In this study, a new combination method “weighted Lancaster method” was proposed by incorporating weights into the statistic of Lancaster method, and an alternative approximation for the distribution of the combined statistic without the condition that combined p-values should be independent is derived. Through simulation studies, we show that the approximation proposed for the distribution of the statistic of weighted Lancaster method works quite well and power of weighted Lancaster method is superior to weighted inverse normal method and Lancaster method under most situations studied whether combined p-values are independent or not.
author2 Hou, Chia-Ding
author_facet Hou, Chia-Ding
Yang, Ti-Sung
楊廸雄
author Yang, Ti-Sung
楊廸雄
spellingShingle Yang, Ti-Sung
楊廸雄
A New Weighted Combination Procedure
author_sort Yang, Ti-Sung
title A New Weighted Combination Procedure
title_short A New Weighted Combination Procedure
title_full A New Weighted Combination Procedure
title_fullStr A New Weighted Combination Procedure
title_full_unstemmed A New Weighted Combination Procedure
title_sort new weighted combination procedure
publishDate 2012
url http://ndltd.ncl.edu.tw/handle/61387979984578930138
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