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广义估计方程中工作相关阵选择准则的比较
  • ISSN号：1001-4268
  • 期刊名称：应用概率统计
  • 时间：2013
  • 页码：515-530
  • 分类：O212.1[理学—概率论与数理统计;理学—数学]
  • 作者机构：[1]复旦大学管理学院统计学系
  • 相关基金：supported by National Natural Science Foundation of China(11271080)
  • 相关项目：应用统计方法研究
作者： 朱晓露|朱仲义|
关键词： 纵向数据, 模型选择, 伪似然, 经验似然, Longitudinal data, model selection, pseudolikelihood, empirical likelihood.
中文摘要：

在本文中，我们比较了广义估计方程中相关阵基于高斯伪似然、修正的高斯伪似然和经验似然的选择方法．通过大量的模拟研究，我们发现修正的高斯伪似然方法优于其他两种方法．对二项离散模型，经验似然方法在选择可交换相关结构时有更好的表现．最后，通过两个实例分析，进一步分析了各个选择方法之间的优劣性．

英文摘要：

In this paper, we compare two modified Gaussian pseudolikelihood criteria （GPCs） with ex- isting Gaussian pseudolikelihood criterion and empirical likelihood based criteria to choose the working correlation matrix in generalized estimating equations approach. Rich simulation studies are conducted to investigate the performance of these criteria under a range of model settings. The results show that the modified criteria outperform the original GPC and empirical likelihood based criteria in most cases in terms of selection accuracy. Empirical likelihood based criteria perform better to identify exchangeable structure in data with binary response. In the end, these criteria are applied to epilepsy seizure and Madras longitudinal schizophrenia study clinical data sets analysis.

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期刊信息
  • 《应用概率统计》
  • 中国科技核心期刊
  • 主管单位:中国科协
  • 主办单位:中国数学会概率统计学会
  • 主编：陈木法
  • 地址：上海市闵行区东川路500号华东师范大学统计学院
  • 邮编：200241
  • 邮箱：aps@stat.ecnu.edu.cn
  • 电话：021-54345267
  • 国际标准刊号：ISSN：1001-4268
  • 国内统一刊号：ISSN：31-1256/O1
  • 邮发代号:4-414
  • 获奖情况:
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  • 被引量:3548