数学学报 2012, 55(1) 1-16 DOI:      ISSN: 0583-1431 CN: 11-2038/O1

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本文关键词相关文章
纵向数据
广义估计方程
经验似然
本文作者相关文章
纵向数据下关于估计方程估计
赵目1,2, 陈柏成3, 周勇1,3
1. 中国科学院数学与系统科学研究院 北京 100190;
2. 安徽大学数学科学学院 合肥 230039;
3. 上海财经大学统管学院 上海 200433
摘要: 广义估计方程方法是一种最一般的参数估计方法, 广泛地应用于生物统计、经济计量、医疗保险等领域.在纵向数据下, 由于组间数据是相关的, 为了提高估计的效率, 广义估计方程方法一般需要考虑个体组内相关性.因此, 大多数文献对个体组内的协方差矩阵进行参数假设,但假设的合理性及协方差矩阵估计的好坏对参数估计效率产生很大影响,同时参数假设也可能导致模型误判.针对纵向数据下广义估计方程, 本文提出了改进的GMM方法和经验似然方法, 并对给出的估计量建立了大样本性质. 其中分块的思想, 避免了对个体组内相关性结构进行假设, 从这种意义上说, 这种方法具有一定的稳健性.我们还通过两个模拟的例子, 考察了文中提出估计量的有限样本性质.  
关键词 纵向数据   广义估计方程   经验似然  
MSC2000 

O212, O212.1

Generalized Estimating Equation Estimators with Longitudinal Data
Mu ZHAO1,2, Bai Cheng CHEN3, Yong ZHOU1,3
1. Academy of Mathematics and Systems Science, Chinese Academy of Sciences, Beijing 100190, P. R. China;
2. School of Mathematical Sciences, Anhui University, Hefei 230039, P. R. China;
3. School of Statistics and Management, Shanghai University of Finance and Economics, Shanghai 200433, P. R. China
Abstract: Generalized estimating equations method as a powerful method for estimating parameters, is wildly used in many fields, such as biostatistics, econometrics and medical insurance, and so on. For longitudinal data, We should take account into within-subject correlation structure in order to improve efficiency of a estimator. It is often useful to suppose that there is a parametric assumption within-subject correlation in longitudinal data analysis. But unreasonable assumptions made on within-subject correlation structure can result in inefficient estimation for parameters or even result in misspecification. For the generalized estimating equations with longitudinal data, we propose the extended GMM methods and extended EL methods and construct the large sample properties for our estimators. One of the proposed EL methods which is called block empirical likelihood is robust because of avoiding any assumptions on withinsubject correlation structure. We also provide two simulation examples to illustrate the finite properties for our estimators.  
Keywords: longitudinal data   generalized estimating equations   empirical likelihood  
收稿日期 2010-09-03 修回日期 2011-07-01 网络版发布日期  
DOI:
基金项目:

国家杰出青年基金(70825004); 国家自然科学基金重点资助项目(10731010); 国家自然科学基金委创新研究群体科学基金(10721101); 国家973项目子项目(2007CB814902); 上海财经大学211工程三期重点学科建设项目; 上海市重点学科建设资助项目(B803)

通讯作者:
作者简介:
作者Email: zhaomu.amss@gmail.com;baicheng.chen@gmail.com;yzhou@amss.ac.cn

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