出版日期：2006-12-01 00:00:00

著者：Cheng, K. F.; Chen, Li-ching

單位：淡江大學統計學系

出版者：Amsterdam: Elsevier BV * North-Holland

著錄名稱、卷期、頁數：Journal of Statistical Planning and Inference 136(12), pp.4147-4160

摘要：Errors in measurement frequently occur in observing responses. If case–control data are based on certain reported responses, which may not be the true responses, then we have contaminated case–control data. In this paper, we first show that the ordinary logistic regression analysis based on contaminated case–control data can lead to very serious biased conclusions. This can be concluded from the results of a theoretical argument, one example, and two simulation studies. We next derive the semiparametric maximum likelihood estimate (MLE) of the risk parameter of a logistic regression model when there is a validation subsample. The asymptotic normality of the semiparametric MLE will be shown along with consistent estimate of asymptotic variance. Our example and two simulation studies show these estimates to have reasonable performance under finite sample situations.

關鍵字：Case–control data; Contamination; Logistic regression; Maximum likelihood; Misclassification

語言：en

ISSN：0378-3758

期刊性質：國外

收錄於：SCI

國別：NLD

出版型式：紙本