博碩士論文 992205026 完整後設資料紀錄

DC 欄位 語言
DC.contributor統計研究所zh_TW
DC.creator陶漢威zh_TW
DC.creatorHan-Wei Tauen_US
dc.date.accessioned2012-7-6T07:39:07Z
dc.date.available2012-7-6T07:39:07Z
dc.date.issued2012
dc.identifier.urihttp://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=992205026
dc.contributor.department統計研究所zh_TW
DC.description國立中央大學zh_TW
DC.descriptionNational Central Universityen_US
dc.description.abstract本文在病例對照研究之下,探求相對於一種既存標準的醫學診斷方法, 另一種嫌究中的醫學診斷方法是否具備非劣性。此一研究中的每一個受試 者皆接受兩種不同的診斷方法,所得到的是具有相關性的成對診斷值。本 文考慮將成對資料利用冪轉換,轉換成近似二元常態分布的資料,然後進 行現有文獻中的有母數非劣性檢定。另一方面,本文應用不同的廣義伽瑪 分布描述右偏分布的二個診斷資料,並且使用適當的關聯結構函數聯結上 述的兩個邊際分布,用以描述成對資料的聯合分布。然後,在此一聯合分 布之下,建構兩條受試者操作特徵曲線,並且根據二條估計的曲線下的部 分面積之差異進行非劣性檢定。本文進一步在不同的關聯結構函數、廣義 伽瑪分邊際分布、相關係數等條件下,藉由模擬研究探討本文所提檢定方 法的型I 誤差率和檢定力表現。最後藉由分析一個實例說明上述檢定方法的 應用。 zh_TW
dc.description.abstractIn this paper, we consider testing the non-inferiority of two medical diagnostic methods in a case-control study where each subject receiving the two different diagnostics produces correlated paired measurements. Note that it occurs often in practice that the marginal distributions of the measurements are right-skewed. Therefore, we first apply the power transformation to the paired data so that they would behave like the bivariate normal data. One parametric non-inferiority test is then implemented based on the transformed data. On the other hand, we suggest and employ appropriate copula function which links two generalized gamma distributions to describe the joint distribution of the paired measurements. Under the joint distribution, an approximate test based on the difference between the partial areas under the two estimated Receiver Operating Characteristic (ROC) curves is then constructed. In this paper, we would like to test if the difference between the true areas is within an allowable region. The results of a simulation investigation of the level and power performances of the approximate test for different degrees of correlation in several possible copula functions with a variety of marginal distributions are reported. Finally, a real data set is illustrated by using the approximate test. en_US
DC.subject非劣性檢定zh_TW
DC.subject關聯結構函數zh_TW
DC.subject廣義伽瑪分布zh_TW
DC.subject受試者操作特徵曲線zh_TW
DC.subjectgeneralized gamma distributionen_US
DC.subjectCopula functionsen_US
DC.title針對受試者操作特徵曲線下部分面積建立的非劣性檢定zh_TW
dc.language.isozh-TWzh-TW
DC.titleNon-inferiority tests based on the partial area under ROC curveen_US
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

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