Orthogonality Based Empirical Likelihood Inferences for Linear Mixed Effects Models
Received:September 06, 2018  Revised:September 04, 2019
Key Word: Linear mixed effects model   orthogonality empirical likelihood   QR decomposition   random effects  
Fund ProjectL:Supported by the National Social Science Foundation of China (Grant No.18BTJ035).
Author NameAffiliation
Changqing LIU College of Mathematics and Statistics, Baise University, Guangxi 533000, P. R. China 
Peixin ZHAO College of Mathematics and Statistics, Chongqing Technology and Business University, Chongqing 400067, P. R. China
Chongqing Key Laboratory of Social Economy and Applied Statistics, Chongqing 400067, P. R. China 
Yiping YANG College of Mathematics and Statistics, Chongqing Technology and Business University, Chongqing 400067, P. R. China 
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Abstract:
      Based on empirical likelihood method and QR decomposition technique, an orthogonality empirical likelihood based estimation method for the fixed effects in linear mixed effects models is proposed. Under some regularity conditions, the proposed empirical log-likelihood ratio is proved to be asymptotically chi-squared, and then the confidence intervals for the fixed effects are constructed. The proposed estimation procedure is not affected by the random effects, and then the resulting estimator is more effective. Some simulations and a real data application are conducted for further illustrating the performances of the proposed method.
Citation:
DOI:10.3770/j.issn:2095-2651.2020.02.009
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