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    Please use this identifier to cite or link to this item: http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/115287

    Title: 病例對照研究中多元羅吉斯模型適合度檢定的比較
    Other Titles: A Comparison of Goodness-Of-Fit Tests of the Multinomial Logistic Regression Model in Case-Control Studies
    Authors: 陳麗菁
    Date: 2018-02-10
    Issue Date: 2018-10-18 12:13:49 (UTC+8)
    Abstract: 多元羅吉斯迴歸模型廣泛地用來推論多元疾病與風險因子之間的關係。本研究擬針對多元反應變數的病例對照資料,以Chen and Wang (2015) 的發現為基礎,將多元羅吉斯迴歸模型視為多組的半參數化模型,從而推廣Qin and Zhang (1997) 的想法到病例對照多元羅吉斯迴歸資料,利用累積分配函數的半參數最大概似估計量和經驗分配之間的差距,提出Kolmogorov-Smirnov形式檢定統計量以評估迴歸模型的配合度;並以拔靴法(bootstrap)求Kolmogorov-Smirnov檢定統計量的臨界值。進一步,本研究亦打算推廣Zhang(2001) 訊息矩陣檢定(information matrix test)的概念到病例對照多元羅吉斯迴歸模型的檢測,利用分數導數矩陣(score derivative matrix)與平方分數矩陣(squared score matrix)的差異來檢視迴歸模型的配適度;並推論訊息矩陣適合度檢定統計量在虛無假設下的漸進分配。本研究的另一個重點為透過大量的模擬研究,以評估這兩個檢定的表現,並與Chen and Wang (2015)的動差形式檢定進行比較。最後將以幾組實際資料示範這些檢定的執行。
    Appears in Collections:[Graduate Institute & Department of Statistics] Research Paper

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