An autoregressive linear mixed effects model for the analysis of longitudinal data which show profiles approaching asymptotes
An autoregressive linear mixed effects model for the analysis of longitudinal data which show profiles approaching asymptotes
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DOI：
10.1002/sim.2670
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发表时间：
2007-04-30
影响因子：
2
通讯作者：
Ohashi, Yasuo
中科院分区：
文献类型：
--
作者：
Funatogawa, Ikuko;Funatogawa, Takashi;Ohashi, Yasuo
在纵向数据中，连续响应有时显示接近渐近线的轮廓。对于这样的数据，我们提出了一类新的模型，自回归线性混合效应模型，其中当前的响应是对先前的响应，固定效应和随机效应进行回归。渐近线可以根据治疗组、个体等发生变化，并且可以通过固定效应和随机效应进行建模。我们还提出了在实践中有用的错误结构。线性混合效应模型的估计方法只要不存在间歇性缺失就可以使用。版权所有（c）2006约翰威利父子有限公司。
In longitudinal data, a continuous response sometimes shows a profile approaching an asymptote. For such data, we propose a new class of models, autoregressive linear mixed effects models in which the current response is regressed on the previous response, fixed effects, and random effects. Asymptotes can shift depending on treatment groups, individuals, and so on, and can be modelled by fixed and random effects. We also propose error structures that are useful in practice. The estimation methods of linear mixed effects models can be used as long as there is no intermittent missing. Copyright (c) 2006 John Wiley & Sons, Ltd.