马尔科夫蒙特卡洛
吉布斯抽样
贝叶斯概率
马尔可夫链
人口
计算机科学
统计
蒙特卡罗方法
计量经济学
数学
医学
环境卫生
作者
Paul Jordan,Hadassa Brunschwig,Eric Luedin
摘要
Abstract The approach of Bayesian mixed effects modeling is an appropriate method for estimating both population‐specific as well as subject‐specific times to steady state. In addition to pure estimation, the approach allows to determine the time until a certain fraction of individuals of a population has reached steady state with a pre‐specified certainty. In this paper a mixed effects model for the parameters of a nonlinear pharmacokinetic model is used within a Bayesian framework. Model fitting by means of Markov Chain Monte Carlo methods as implemented in the Gibbs sampler as well as the extraction of estimates and probability statements of interest are described. Finally, the proposed approach is illustrated by application to trough data from a multiple dose clinical trial. Copyright © 2007 John Wiley & Sons, Ltd.
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