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研究生:張暐文
研究生(外文):Wei-Wen Chang
論文名稱:探討二元資料組內相關不同估計方法之效率
論文名稱(外文):The Efficiency of Intraclass Correlation Estimating for Binary Data
指導教授:陳世雄陳世雄引用關係
指導教授(外文):Shih-Shiung Chen
學位類別:碩士
校院名稱:國立中興大學
系所名稱:農藝學系
學門:農業科學學門
學類:一般農業學類
論文種類:學術論文
論文出版年:2005
畢業學年度:93
語文別:中文
外文關鍵詞:Intraclass correlation coefficientICCcommon correlation modelexchangeabilitycoverage rate
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Binary data occur frequently in research of epidemiology, sociology, biology and so forth, such as studies of familial diseases and repeated measurement studies and like versa. In these conditions, there is a correlation between these observations. The intraclass correlation coefficient (ICC) is a quantitative measure of the resemblance among observations within clusters. At least 20 different point estimators of the ICC have been proposed in various areas of application. However, techniques for binary data have been less developed. And the efficiency and application of these techniques are differ from each other.
The main purposes of this research aimed to estimate the intraclass correlation coefficient and to evaluate the efficiency of the three ICC methods for binary data proposed by Ridout et al. (1999). Base on common correlation model, computer simulation is applied to compare these three methods in this research. All the simulations in this article are implemented by using the program language of Visual Basic. According to the changes of the three parameters (i.e. intraclass correlation coefficient ρ, the probability of success π, and number of clusters k), the performances of each method are discussed under different parameter combinations.
Simulation results indicated that the coverage of confidence interval obtained from ANOVA method performed well only when ρ is small. However, it is not stable under other parameter combinations. On the other hand, the coverage of confidence interval based on the Pearson and the FC estimates for ρ, showed highly stable under any combinations of parameter. In general, the coverage levels of the three methods are low when k is small. Even k is increasing, the coverage rates perform not ideally when the ρ is extreme (ρ is close to 0 or 1). Thus, research requires these three methods to apply in certain particular situations, such as sample size is small or extremely high or low intraclass correlation, the correlation coefficients and confidence intervals estimated by these methods should not be credible.
中文摘要…………………………………………………………………i
英文摘要……………………………………………………………........ii

第一章 緒論............…............................................................................1
1.1 研究背景……………………………………………………….1
1.2 組內相關係數推論方法……………………………………….1
1.3 研究動機與目的……………………………………………….3
第二章 研究方法與理論架構………………………………………....4
2.1 理論假設與基本模型………………………………………….4
2.2 ICC估計式介紹………………………………………………...5
2.3 變異數的衍生………………………………………………….9
2.4 信賴區間的建構……………………………………………...11
第三章 模擬研究……………………………………………………..13
3.1 觀測值的產生………………………………………………...13
3.2 模擬組合……………………………………………………...14
3.3 模擬方法……………………………………………………...14


第四章 模擬結果……………………………………………………..18
4.1 三種方法之覆蓋率比較……………………………………...18
4.2 參數變化對覆蓋率的影響…………………………………...24
4.3 群集大小(n)對覆蓋率的影響………………………………..33
4.4 實例應用……………………………………………………...37
第五章 討論…………………………………………………………..40
第六章 結論…………………………………………………………..44
參考文獻………………………………………………………………..45
附錄……………………………………………………………………..49
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