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    政大機構典藏 > 商學院 > 統計學系 > 期刊論文 >  Item 140.119/72217
    Please use this identifier to cite or link to this item: http://nccur.lib.nccu.edu.tw/handle/140.119/72217


    Title: Correcting bias due to misclassification in the estimation of logistic regression models
    Authors: Hsueh,Huey-Miin;Cheng, K. F.
    薛慧敏
    Contributors: 統計系
    Date: 1999-09
    Issue Date: 2014-12-23 15:09:01 (UTC+8)
    Abstract: This paper describes several properties of some bias correction methods in the estimation of logistic regression models with misclassification in the binary responses. The observation error model consists of a primary data set plus a smaller validation set. The large sample properties of different bias correction methods are compared under various situations, and the asymptotic relative efficiencies of some important methods are derived. Our small sample simulation studies conclude that the semiparametric estimation method considered by Pepe (Biometrika 79(1992)355–365) is quite reliable under a reasonable surrogate classifier.
    Relation: Statistics & Probability Letter,44(3), 229-240
    Data Type: article
    Appears in Collections:[統計學系] 期刊論文

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