博碩士論文 105225021 完整後設資料紀錄

DC 欄位 語言
DC.contributor統計研究所zh_TW
DC.creator李怡萱zh_TW
DC.creatorYi-Hsuan Leeen_US
dc.date.accessioned2018-6-29T07:39:07Z
dc.date.available2018-6-29T07:39:07Z
dc.date.issued2018
dc.identifier.urihttp://ir.lib.ncu.edu.tw:88/thesis/view_etd.asp?URN=105225021
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本文在診斷結果有三種可能的情況下,針對群集成對資料下的kappa 參數及加權 kappa 參數進行推論,建立kappa 參數之強韌概似函數。利用此強韌概似函數,在不需要特別對於群集間的相關性建立模型假設下,仍可以得到概似比檢定統計量及根據概似比檢定統計量所得到的信賴區間等正確的推論結果。同時,我們將用模擬與實例分析來比較我們的強韌推論方法與Yang and Zhou (2014, 2015)分別提出的在群集成對資料下的kappa 及加權kappa 的無母數推論方法。zh_TW
dc.description.abstractIn this paper, we construct a robust likelihood function for the agreement kappa/weighted kappa coefficient for clustered paired data in the case of three-category diagnostic outcome scenario. Utilizing this robust likelihood function, one can construct robust likelihood ratio (LR) statistic and LR-based confidence intervals without specifically modeling the intra-cluster correlation. We also make comparison between our robust likelihood approach and the nonparametric inferential method for kappa with paired data proposed by Yang and Zhou (2014, 2015) via simulations and real data analysis.en_US
DC.subject相關性資料zh_TW
DC.subject一致性Kappazh_TW
DC.subject強韌概似函數zh_TW
DC.subjectCorrelated dataen_US
DC.subjectAgreement Kappaen_US
DC.subjectRobust likelihood functionen_US
DC.title成對資料下名目與有序資料一致性kappa 參數的強韌概似分析zh_TW
dc.language.isozh-TWzh-TW
DC.titleRobust likelihood analysis of the agreement kappa coefficient for paired nominal and paired ordinal dataen_US
DC.type博碩士論文zh_TW
DC.typethesisen_US
DC.publisherNational Central Universityen_US

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