頁籤選單縮合
題 名 | Efficient Estimation for the Proportional Hazards Model with Left-Truncated and "Case 1" Interval-Censored Data |
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作 者 | Kim,Jong S.; | 書刊名 | Statistica Sinica |
卷 期 | 13:2 2003.04[民92.04] |
頁 次 | 頁519-537 |
分類號 | 319 |
關鍵詞 | Asymptotic distribution; Left-truncated and "Case 1" interval-censored data; Proportional hazards model; Variance estimation; |
語 文 | 英文(English) |
英文摘要 | The maximum likelihood estimator (MLE) for the proportional hazards model with left-truncated and “Case 1” interval-censored data is studied. Under appropriate regularity conditions, the MLE of the regression parameter is shown to be asymptotically normal with a root-n convergence rate and achieves the information bound, even though the difference between left-truncation time and censoring time of the MLE of the baseline cumulative hazard function converges only at rate n^1/3. Two methods to estimate the variance-covariance matrix of the MLE of the regression parameter are considered. One is based on a generalized missing information principle and the other is based on the profile information procedure. Simulation studies show that both methods work well in terms of bias and variance for samples of moderate sizes. An example is provided to illustrate the methods. |
本系統中英文摘要資訊取自各篇刊載內容。