頁籤選單縮合
題名 | Bayesian Accelerated Failure Time Model for Correlated Interval-Censored Data with a Normal Mixture as Error Distribution= |
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作者 | Komárek, Arnošt; Lesaffre, Emmanuel; |
期刊 | Statistica Sinica |
出版日期 | 20070400 |
卷期 | 17:2 2007.04[民96.04] |
頁次 | 頁549-569 |
分類號 | 319.51 |
語文 | eng |
關鍵詞 | Clustered data; Multicenter study; Regression; Reversible jump Markov chain Monte Carlo; Survival data; |
英文摘要 | A Bayesian approach is proposed for an accelerated failure time model with interval-censored data. The model allows for structured correlated data by inclusion of a random effect part that might depend on covariates, as in a linear mixed model. The error distribution is modeled as a normal mixture with an unknown number of components. Also, the means and variances of the components are not prespecified so as to accommodate most continuous distributions. This results, among other things, in a nearly correct estimation oft eh shape of the hazard and survivor curves. A Markov chain Monte Carlo algorithms is described that samples from the posterior distribution. The approach is evaluated using a simulation study, and is illustrated by modeling the emergence times of eight permanent teeth using data from the Signal Tandmobiel study. |
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