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Testing for random effects in linear mixed models for longitudinal data under moment conditions |
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| Authors: | Zai Xing Li Li Xing Zhu Ping Wu Jian Hong Wu Wang Li Xu |
| Affiliation: | 1. Department of Mathematics, China University of Mining & Technology, Beijing, 100083, P. R. China 2. Department of Mathematics, Hong Kong Baptist University, Hong Kong, P. R. China 3. School of Finance and Statistics, East China Normal University, Shanghai, 200241, P. R. China 4. College of Statistics and Mathematics, Zhejiang Gongshang University, Hangzhou, 310018, P. R. China 5. School of Statistics, Renmin University of China, Beijing, 100872, P. R. China |
| Abstract: | 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. |
| Keywords: | consistent estimators asymptotic normality LMMs random effects |
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