頁籤選單縮合
題 名 | Frailty Model with Spline Estimated Nonparametric Hazard Function |
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作 者 | Du, Pang; Ma, Shuangge; | 書刊名 | Statistica Sinica |
卷 期 | 20:2 2010.04[民99.04] |
頁 次 | 頁561-580 |
分類號 | 319.5 |
關鍵詞 | Bayesian confidence intervals; Cross-validation; Frailty; Hazard; Model selection; Penalized likelihood; |
語 文 | 英文(English) |
英文摘要 | Abstract: Frailty has been introduced as a group-wise random effect to describe the within-group dependence for correlated survival data. In this article, we propose a penalized joint likelihood method for nonparametric estimation of hazard function. With the proposed method, the frailty variance component and the smoothing parameters become the tuning parameters that are selected to minimize a loss function derived from the Kullback-Leibler distance through delete-one cross-validation. Confidence intervals for the hazard function are constructed using the Bayes model of the penalized likelihood. Combining the functional ANOVA decomposition and the Kullback-Leibler geometry, we also derive a model selection tool to assess the covariate effects. We establish that our estimate is consistent and its nonparametric part achieves the optimal convergence rate. We investigate finite sample performance of the proposed method with simulations and data analysis. |
本系統中英文摘要資訊取自各篇刊載內容。