本文探討當邏輯斯模型的自變數有測量誤差時,各種不同的估計方法表現的模擬研究。這些方法包含了傳統的迴歸校正、條件分數及新穎的延伸校正分數函數等等。我們考慮有不同的自變數分佈、樣本大小、迴歸參數值、測量誤差變異數與測量誤差分佈等許多情況,並從估計量的樣本變異數或是標準差的大小來評估不同估計方法的效率。 This thesis discusses the performances of different estimation methods in logistic regression model when covariates are subject to measurement errors. The efficiencies of different methods were evaluated through extensively simulation studies. These simulation studies were conducted under different distribution of covariates, samples size, values of regression parameter, the variance associated with measurement errors and the distribution of measurement errors. Conclusions based on the sample standard deviations were derived.