基于M估计的指数相关非线性混合效应模型的齐性检验

摘要

方差和相关系数的齐性是纵向数据分析中常用假设之一,然而,这些假设未必合适.本文主要研究的是具有指数相关结构的纵向数据非线性混合效应模型,首先将Huber函数引入模型的对数似然函数中,利用Fisher得分迭代法得到模型参数的稳健估计(M估计),然后基于M估计对模型的方差和相关系数的齐性进行了Score检验,并给出了检验统计量的Monte-Carlo模拟结果.最后用一个实例说明了本文的方法.%Homogeneity of variance and correlation coefficients is one of assumptions in the analysis of longitudinal data.However,the assumption can be challenged.In this paper,we mainly propose and analyze nonlinear mixed effects models for longitudinal data with exponential correlation covariance structure,intend to introduce Huber's function in the log likelihood function and get robust estimation (M-estimation) by Fisher scoring method.Score test statistics for homogeneity of variance and correlation coefficient based on M-estimation are then studied.A simulation study is carried to assess the performance of test statistics and the method we proposed in the paper is illustrated by an actual data example.