Testing for Random Effects in Linear Mixed Models for Longitudinal Data under Moment Conditions

作     者：Zai King LI Li Xing ZHU Ping WU Jian Hong WU Wang Li XU 

作者机构：Department of Mathematics China University of Mining & Technology Beijing 100083 P. R. China Department of Mathematics Hong Kong Baptist University Hong Kong P. R. China School of Finance and Statistics East China Normal University Shanghai 200241 P. R. China College of Statistics and Mathematics Zhejiang Gongshang University Hangzhou 310018 P. R. China School of Statistics Renmin University of China Beijing 100872 P. R. China 

出 版 物：《Acta Mathematica Sinica,English Series》 (数学学报（英文版）)

年 卷 期：2010年第26卷第3期

页      面：497-514页

核心收录：

学科分类：0821[工学-纺织科学与工程] 02[经济学] 0202[经济学-应用经济学] 020208[经济学-统计学] 07[理学] 08[工学] 0714[理学-统计学（可授理学、经济学学位）] 070103[理学-概率论与数理统计] 082101[工学-纺织工程] 0701[理学-数学] 

基　　金：Supported by a grant (HKBU2030/07P) from the Research Grants Council of Hong Kong the National Natural Science Foundation of China (Grant No. 10871001) the Humanities and Social Sciences Project of Chinese Ministry of Education (Grant No. 08JC910002) Zhejiang Provincial Natural Science Foundation of China (Grant No. Y6090172) Youth Talent Foundation of Zhejiang Gongshang University, China 

主　　题：consistent estimators asymptotic normality LMMs random effects 

摘      要：In this paper, we consider whether the random effect exists in linear mixed models （LMMs） when only moment conditions are assumed. Based on the estimators of parameters and their asymptotic properties, a Wald-type test is constructed. It is consistent against global alternatives and is sensitive to the local alternatives converging to the null hypothesis at parametric rates, a fastest possibly rate for goodness-of-fit testing. Moreover, a simulation study shows the performance of the test is good. The procedure also applies to a real data.