姓名 |
李怡萱(Yi-Hsuan Lee)
查詢紙本館藏 |
畢業系所 |
統計研究所 |
論文名稱 |
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 (Robust likelihood analysis of the agreement kappa coefficient for paired nominal and paired ordinal data)
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相關論文 | |
檔案 |
[Endnote RIS 格式]
[Bibtex 格式]
[相關文章] [文章引用] [完整記錄] [館藏目錄] 至系統瀏覽論文 ( 永不開放)
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摘要(中) |
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。 |
摘要(英) |
In 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. |
關鍵字(中) |
★ 相關性資料 ★ 一致性Kappa ★ 強韌概似函數 |
關鍵字(英) |
★ Correlated data ★ Agreement Kappa ★ Robust likelihood function |
論文目次 |
摘要 ............................................................................................................................................ i
Abstract ...................................................................................................................................... ii
誌謝辭 ...................................................................................................................................... iii
目錄 .......................................................................................................................................... iv
表目錄 ....................................................................................................................................... v
第一章 緒論 .............................................................................................................................. 1
第二章 文獻回顧 ...................................................................................................................... 7
2.1 資料( ,1 , ,2 ) i i X X 與,1 ,2 ( , ) i i Y Y 為獨立時κ 之變異數估計量 ......................................... 7
2.2 資料,1 ,2 ( , ) i i X X 與,1 ,2 ( , ) i i Y Y 具有相關性時κ 之變異數估計量 ................................. 9
2.3 資料,1 ,2 ( , ) i i X X 與,1 ,2 ( , ) i i Y Y 為獨立時κw 之變異數估計量 ..................................... 11
2.4 資料,1 ,2 ( , ) i i X X 與,1 ,2 ( , ) i i Y Y 具有相關性時κw 之變異數估計量 ............................. 13
第三章 多項模型之強韌化 .................................................................................................... 14
3.1 參數之最大概似估計量其一致性成立 ................................................................... 17
3.2 修正項A .................................................................................................................... 21
3.3 修正項B .................................................................................................................... 21
第四章 模擬研究 .................................................................................................................... 23
第五章 實例分析 .................................................................................................................... 56
第六章 結論 ............................................................................................................................ 59
參考文獻 ................................................................................................................................. 60
附錄A ..................................................................................................................................... 61
附錄B ..................................................................................................................................... 71
附錄C ................................................................................................................................... 119 |
參考文獻 |
Bishop Y.M.M., Fienberg S.E., and Holland P.W. (1975). Discrete Multivariate Analysis: Theory and Practice. Cambridge:Massachusetts Institute of Technology Press.
Cicchetti D., Allison T., (1971). A new procedure for assessing reliability of scoring EEG sleep recordings. American Journal,EEG Technology, 11 (3): 101–109.
Cohen J. (1960). A coefficient of agreement for nominal scales. Educational and Psychological Measurement, 20 (1): 37-46.
Cohen J. (1968). Weighted kappa: Nominal scale agreement provision for scaled disagreement or partial credit. Psychological. Bulletin, 70 (4): 213-220.
Fleiss J.L., Cohen J., Everitt B.S. (1969). Large sample standard errors of kappa and weighted kappa. Psychological. Bulletin, 72 (5): 323-327.
Fleiss J.L., Cohen J. (1973). The equivalence of weighted kappa and the intraclass correlation coefficient as measure of reliability. Educational and Psychological. Measurement, 33 (3): 613–619.
Landis, J.R.and Koch, G.G. (1977). The measurement of observer agreement for categorical data. Biometrics, 33 (1): 159–174.
Royall R. and Tsou T.S. (2003). Interpreting statistical evidence by using imperfect models: robust adjusted likelihood functions. Journal of the Royal Statistical Society, Series B, 65 (2): 391-404.
Yang Z. and Zhou M. (2014). Kappa statistic for clustered matched-pair data. Statistics in Medicine, 33 (15): 2612-2633.
Yang Z. and Zhou M. (2015). Weighted kappa statistic for clustered matched-pair ordinal data. Computational Statistics and Data Analysis, 82: 1-18. |
指導教授 |
鄒宗山(Tsung-Shan Tsou)
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審核日期 |
2018-6-29 |
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