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姓名	劉亞幸(Ya-Hsing Liu)  查詢紙本館藏	畢業系所	數學系
論文名稱	在只有部份疾病訊息狀況下,有關二元診斷篩檢法之二個概似比特徵之概似推論方法 (Likelihood methods for inference about the likelihood ratios of a binary diagnostic test in the presence of partial disease verification)
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)
摘要(中)	在醫學研究中，常使用二元診斷法來估計正概似比(positive likelihood ratio)與負概似比(negative likelihood ratio)，當遇到疾病訊息缺失時，要估計正概似比與負概似比往往相對困難些，本文針對疾病訊息是否有缺失時提出了概似函數方法。在獨立的伯努利概似函數推論下，可得到分數檢定、華德檢定與概似檢定。本文利用模擬與實例分析分別比較概似函數方法、Montero-Alonso與Roldan-Nofuentes (2018) 提出的華德檢定、Simel et al. (1991) 納皮爾概似比檢定與Walter (1975) 概似比檢定的型一誤差的機率、信賴區間上下界與覆蓋率，可發現本文的模型在解決疾病訊息缺失問題中更具優勢。
摘要(英)	In medical research, the classic parameters use to assess the accuracy of a binary diagnostic test are the positive likelihood ratio and the negative likelihood ratio.The presence of missing data, When the disease information is missing, the positive likelihood ratio and the negative likelihood ratio are difficult to estimation.The article considers the disease information is missing or not, proposd the likelihood function method. The article use independent binary likelihood function, inferenced score test, wald test and likelihood ratios test statistics.We use simulation and real data analysis to demonstrate the merit of our new parametric robust technique. We also make comparison with to the wald test proposed by Montero-Alonso and Roldan-Nofuentes (2018), the Napierian likelihood test statistics proposed by Simel et al. (1991) and the likelihood test statistics proposed by Walter (1975).
關鍵字(中)	★ 概似函數 ★ 二元資料 ★ 驗證偏差 ★ 疾病訊息缺失	關鍵字(英)	★ Likelihood ratio test ★ Binary data ★ Verification bias ★ Missing data
論文目次	摘要 I ABSTRACT II 致謝辭 III 目錄 IV 表目錄 VI 第一章 緒論 1 第二章 文獻回顧 2 2.1 MONTERO-ALONSO與ROLDAN-NOFUENTES (2018) 2 2.2 SIMEL ET AL. (1991) 2 2.3 WALTER (1975) 2 第三章 兩個獨立伯努力模型 3 3.1參數之最大概似估計量 4 3.2 變異數之計算 5 3.3 參數之變異數估計量 6 3.4 參數之分數統計量 7 3.5 參數之概似比統計量 9 第四章 不知道疾病訊息之獨立伯努力模型 10 4.1參數之最大概似估計量 12 4.2 變異數之計算 14 4.3參數之變異數估計量 17 4.4 參數之分數統計量 19 4.5 參數之概似比統計量 20 第五章 模擬研究 22 5.1資料生成方式 22 5.2推算信賴區間之方式 22 5.3模擬結果 26 第六章 實例分析 106 第七章 總結 114 參考文獻 115
參考文獻	[1] Alonso, M. A., Nofuentes, J. A.(2019). Approximate confidence intervals for the likelihood ratios of a binary diagnostic test in the presence of partial disease verification, Journal of Biopharmaceutical Statistics, 29 (1), 56 – 81. [2] Andrzej, S. K., Huiman, X. B. (2003).A global sensitivity analysis of performance of a medical diagnostic test when verification bias is present.Statistics ,22:2711-21 [3] Cecil, M. P. , Kosinski, A. S., Jones, M. T. , Taylor, A. , Alazraki , N. P. , Pettigrew, R. I. , Weintraub, W. S. (1996). The importance of work-up (verification) bias correction in assessing the accuracy of SPECT thallium-201 testing for the diagnosis of coronary artery disease. Journal of Clinical Epidemiology; 49:735–742. [4] Roldan Nofuentes, J. A., Luna del Castillo, J. D., Femia Marzo, P. (2009). Computational methods for comparing two binary diagnostic tests in the presence of partial verification of the disease.Computational Statistics,24:695-718 [5] Royall, R. M. and Tsou, T. S. (2003). Interpreting Statistical Evidence by Using Imperfect Models: Robust Adjusted Likelihood Functions, Journal of the Royal Statistical Society. Series B, 65:391-404 [6] Simel, D. L., Samsa, G. P., Matchar, D. B. (1991). Likelihood ratios with confidence: Sample size estimation for diagnostic test studies. Journal of Clinical Epidemiology, 44:763–770. [7] Strax, P., Venet, L. , Shapiro, S. , Gross, S. (1967). Mammography and clinical examination in mass screening for cancer of breast.Cancer, 20:2184–2188. [8] Walter, S. D. (1975). The distribution of Levin’s measure of attributable risk. Biometrika, 62:371–374. [9] Zhou X .(1998). Comparing accuracies of two screening tests in a two-phase study for dementia. Appl Stat ,47:135–147.
指導教授	許正雄 鄒宗山(Cheng-Hsiung Hsu Tsung-Shan Tsou)	審核日期	2021-7-28
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