共變量測量誤差問題在現狀數據近來已被研究(Wen, Huang和Chen 2011; Wen和Chen 2012)，但對具有免疫子群的此類數據卻還未被探討。研究動機源自台灣2005年『國民健康訪問調查』的糖尿病資料，其中糖尿病發生時間是現狀設限的、共變量身體質量指數具有測量誤差且部分受訪者似乎對糖尿病是免疫的，我們在比例勝算比治癒模型下建立條件分數法來分析具共變量測量誤差之部份免疫現狀數據。條件分數法沒有對易有測量誤差的共變量做分佈的假設因而能有更廣泛的應用。我們藉由模擬研究評估所提方法並以糖尿病資料說明其應用。 Covariate measurement error problem has been recently studied in the context of current status data (Wen, Huang, and Chen 2011; Wen and Chen 2012) but not yet for such data with an immune subgroup. Motivated by the diabetes dataset from the 2005 National Health Interview Survey of Taiwan, where the occurrence time of diabetes was current status censored, covariate Body Mass Index was measured with error, and a fraction of participants seemed immune from diabetes, we develop a conditional score method under the proportional odds cure model for analyzing partially immune current status data with mismeasured covariates. The conditional score approach makes no distribu- tional assumption on the error-prone covariate and hence enjoys wide application. We evaluate the proposed method through simulation studies and illustrate it with the diabetes data.
