雖然已有相當多的研究工作在右設限存活數據具共變量測量誤差的問題，但具共變量測量誤差現狀數據的迴歸分析近年來才開始。這篇論文中，我們考慮Wen and Chen (2012) 分析具共變量誤差現狀數據的條件分數法。不同於Wen and Chen (2012)，我們使用篩選法去近似比例勝算比模型的基線勝算比函數。我們所提方法的優點為條件分數估計的計算更有效率且迴歸係數估計之變異數估計無需估計設限時間分布。所提的方法藉由模擬試驗評量且由一實際數據說明其應用。 While there is considerable work on covariate measurement error problem for right-censored survival data, regression analysis for current status data with mismeasured covariate has just started recently. In this thesis, we consider the conditional score approach of Wen and Chen (2012) for the analysis of errors-in-variable current status data. Distinct from Wen and Chen (2012), we employ a sieve method to approximate the baseline odds ratio function in the proportional odds model. Our proposal has advantages that the computation of conditional score estimates is more efficient and the variance estimation of regression parameter estimate is exempted from estimating the distribution of censoring time. The proposed method is evaluated through simulation studies and illustrated with a real data.