NONLINEAR MIXED EFFECTS MODELS FOR REPEATED MEASURES DATA
NONLINEAR MIXED EFFECTS MODELS FOR REPEATED MEASURES DATA
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DOI：
10.2307/2532087
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发表时间：
1990-09-01
期刊：
影响因子：
1.9
通讯作者：
BATES, DM
中科院分区：
文献类型：
--
作者：
LINDSTROM, MJ;BATES, DM
我们提出了一个一般的，非线性的重复测量数据的混合效应模型，并定义其参数的估计。所提出的估计是非线性固定效应模型的最小二乘估计和线性混合效应模型的最大似然（或限制最大似然）估计的自然组合。我们实现牛顿-拉夫森估计使用以前开发的计算方法的非线性固定效应模型和线性混合效应模型。两个例子，这项工作和最近的工作广义线性混合效应模型之间的联系进行了讨论。
We propose a general, nonlinear mixed effects model for repeated measures data and define estimators for its parameters. The proposed estimators are a natural combination of least squares estimators for nonlinear fixed effects models and maximum likelihood (or restricted maximum likelihood) estimators for linear mixed effects models. We implement Newton-Raphson estimation using previously developed computional methods for nonlinear fixed effects models and for linear mixed effects models. Two examples are presented and the connections between this work and recent work on generalized linear mixed effects models are discussed.