相關性二分法資料迴歸之樣本數的問題; Robust sample size formulae for testing the regression parameter when binary data are correlated

Please use this identifier to cite or link to this item: http://ir.lib.ncu.edu.tw/handle/987654321/7730

Title:	相關性二分法資料迴歸之樣本數的問題;Robust sample size formulae for testing the regression parameter when binary data are correlated
Authors:	王睿愛;Ruei-Ai Wang
Contributors:	統計研究所
Keywords:	二分類相關性資料;邏輯斯迴歸;binary data are correlated;logistic regression
Date:	2008-06-07
Issue Date:	2009-09-22 11:03:22 (UTC+8)
Publisher:	國立中央大學圖書館
Abstract:	摘要本論文研究之目的是利用Royall and Tsou (2003)所介紹的強韌概似函數的概念，提出利用二項分配來分析具相關性的二分法資料時，想要達到一定的檢定力所需要的正確樣本數公式。我們的研究以三種不同的邏輯斯迴歸為例，結果顯示，根據二項分配實作模型所得到的樣本數遠小於正確的樣本數。模擬研究與實例分析也都得到相同的結果。 Abstract The aim of this research is to make use of the robust likelihood method proposed by Royall and Tsou (2003) to establish sample size formulae for testing parameter in logistic regression when binary data are correlated. We adopted the binomial distribution as the working model and robustified the naïve likelihood using the robust technique by Royall and Tsou (2003). Robust sample size formulae for testing the regression parameter associated with the cluster-specific covariate is provided. The two versions of the sample size required to achieve a predetermined power, namely, the naïve and the robust formulae, are compared through simulations and analyses of several real data sets.
Appears in Collections:	[Graduate Institute of Statistics] Electronic Thesis & Dissertation

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