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• W2108507654 abstract "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 modelled as a normal mixture with an un- known number of components. Also, the means and variances of the components are not prespecified so as to accommodate most continuous distributions. This re- sults, among other things, in a nearly correct estimation of the shape of the hazard and survivor curves. A Markov chain Monte Carlo algorithm is described that sam- ples 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 r study." @default.
• W2108507654 created "2016-06-24" @default.
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• W2108507654 date "2007-04-01" @default.
• W2108507654 modified "2023-09-26" @default.
• W2108507654 title "BAYESIAN ACCELERATED FAILURE TIME MODEL FOR CORRELATED INTERVAL-CENSORED DATA WITH A NORMAL MIXTURE AS ERROR DISTRIBUTION" @default.
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