Please use this identifier to cite or link to this item:
https://ah.lib.nccu.edu.tw/handle/140.119/72217
題名: | Correcting bias due to misclassification in the estimation of logistic regression models | 作者: | Hsueh,Huey-Miin;Cheng, K. F. 薛慧敏 |
貢獻者: | 統計系 | 日期: | Sep-1999 | 上傳時間: | 23-Dec-2014 | 摘要: | 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. | 關聯: | Statistics & Probability Letter,44(3), 229-240 | 資料類型: | article |
Appears in Collections: | 期刊論文 |
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229-240.pdf | 134.72 kB | Adobe PDF2 | View/Open |
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