期刊論文
| 學年 | 102 |
|---|---|
| 學期 | 2 |
| 出版（發表）日期 | 2014-06-01 |
| 作品名稱 | Semiparametric analysis of incomplete current status outcome data under transformation models |
| 作品名稱（其他語言） | |
| 著者 | Wen, Chi-Chung; Chen, Yi-Hau |
| 單位 | 淡江大學數學學系 |
| 出版者 | Chichester: Wiley-Blackwell Publishing Ltd. |
| 著錄名稱、卷期、頁數 | Biometrics 70(2), pp.335-345 |
| 摘要 | This work, motivated by an osteoporosis survey study, considers regression analysis with incompletely observed current status data. Here the current status data, including an examination time and an indicator for whether or not the event of interest has occurred by the examination time, is not observed for all subjects. Instead, a surrogate outcome subject to misclassification of the current status is available for all subjects. We focus on semiparametric regression under transformation models, including the proportional hazards and proportional odds models as special cases. Under the missing at random mechanism where the missingness of the current status outcome can depend only on the observed surrogate outcome and covariates, we propose an approach of validation likelihood based on the likelihood from the validation subsample where the data are fully observed, with adjustments of the probability of observing the current status outcome, as well as the distribution of the surrogate outcome in the validation subsample. We propose an efficient computation algorithm for implementation, and derive consistency and asymptotic normality for inference with the proposed estimator. The application to the osteoporosis survey data and simulations reveal that the validation likelihood performs well; it removes the bias from the “complete case” analysis discarding subjects with missing data, and achieves higher efficiency than the inverse probability weighting analysis. |
| 關鍵字 | |
| 語言 | en |
| ISSN | 1541-0420 |
| 期刊性質 | 國外 |
| 收錄於 | SCI |
| 產學合作 | |
| 通訊作者 | Chen, Yi-Hau |
| 審稿制度 | 是 |
| 國別 | GBR |
| 公開徵稿 | |
| 出版型式 | ,電子版 |
| 相關連結 |
機構典藏連結 ( http://tkuir.lib.tku.edu.tw:8080/dspace/handle/987654321/99698 ) |