MODELING PHARMACOKINETIC DATA USING HEAVY-TAILED MULTIVARIATE DISTRIBUTIONS 期刊名称： Journal of Biopharmaceutical Statistics
好书推荐小学生作者： J.,K.,Lindy,B.,Jones
作者机构： Department
年份： 2000年红烧葛鱼
期号： 第3期
关键词： Autocorrelation;Crossover trial;Integrated Ornstein–Uhlenbeck
高兴的事process;Multivariate elliptical distributions;Variance components
摘要：Pharmacokinetic studies of drug and metabolite concentrations in the blood are usually conducted as crossover trials, especially in Phas I and II. A longitudinal ries of measurements is collected on each subject within each period. Dependence among such obrvations, within and betwe中国旅游局
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en periods, will generally be fairly complex, requiring two levels of variance components, for the subjects and for the periods within subjects, and an autocorrelation within periods as well as a time-varying variance. Until now, the standard way in which this has been modeled is using a multivariate normal distribution. Here, we introduce procedures for simultaneously handling the various types of dependence in a wider class of distributions called the multivariate power exponential and Student t families. They can have the heavy tails
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