本文共分六章第一章導論說明線型計量迴歸模式變數誤差的意義。並比較普通最小平方法直接應用於含變數誤差模式及不含變數誤差模式，所得估計式有何不同。第二章提出最大概似法分自變數的真值為固定數值或隨機變數來處理含有變數誤差的線型計量迴歸模式。第三章提出一種不含常態分配的假設，以及計算簡便的方法—觀測資料之分組法。並將此方法所具備的Wald's條件和Neyman-Scott的條件加以比較說明。第四章為工具變數法，找出一組工具變數以代替原來與干擾項相關的自變數，並對其所具備的條件、特性及限制詳加說明。第五章提出貝氏定理有關的觀念以分析變數誤差的問題，利用Jeffreys所提出事前機率密度函數的假設來估計未知母數。第六章結論將上述各種方法加以綜合說明並加以補充。
本論文之撰寫蒙指導教授林憲博士的鼓勵與悉心指導，啟迪釋疑，使本文得以順利完成，謹致最崇高的敬意與謝意。又所主任祁富生教授多方的關懷與督促，鄭師堯柈祁師和福有關統計學識的啓發與多年來諄諄教導，學生不勝感激。此外並向其他教授與同學，致教誨與鼓勵之謝意。學生學識淺陋，文中錯漏之處勢必不少，尚祈諸師長、先進不吝賜正，是所企盼!

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