摘要(中) |
本文主要在研究當二元資料來自病例對照研究時,我們如何估計迴歸參數並檢定羅吉斯迴歸模型的適合度。在一階段病例對照研究中, 我們提出一個新的分數型式檢定方法來檢定模型的適合度,此檢定統計量不僅能避免既有的檢定統計量的缺點,且在我們討論的情形下,具有較高的近似檢定力及較好的有限樣本性質。
當無法取得完整資料時, 我們考慮二階段抽樣設計, 以取得一個有效完整的子樣本。在解釋變數不完全下, 即解釋變數有測量誤差存在或是有遺失值發生時, 本文針對迴歸參數的估計及模型適合度檢定問題,均討論提供合理可行的統計分析方法。 在反應變數不完全下, 即反應變數有錯誤分類時, 本文亦針對迴歸參數的估計,提供半參數最大概似估計量(semiparametric maximum likelihood estimate, SMLE)。 |
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