Standard Error of the Method of Simulated Moment Estimator for Generalized Linear Mixed Models

نویسنده

  • Yan Lu
چکیده

This article may be used for research, teaching, and private study purposes. Any substantial or systematic reproduction, redistribution, reselling, loan, sub-licensing, systematic supply, or distribution in any form to anyone is expressly forbidden. The publisher does not give any warranty express or implied or make any representation that the contents will be complete or accurate or up to date. The accuracy of any instructions, formulae, and drug doses should be independently verified with primary sources. The publisher shall not be liable for any loss, actions, claims, proceedings, demand, or costs or damages whatsoever or howsoever caused arising directly or indirectly in connection with or arising out of the use of this material. This article considers standard error estimation of the method of simulated moment estimator for generalized linear mixed models. In literature, parametric bootstrap is used to estimate the covariance matrix, in which we use the estimator to generate simulated moments. To avoid the bias introduced by estimating the parameter and to deal with the correlated observations, we propose a two-stage block nonparametric bootstrap to estimate the standard errors. It is shown from simulation study that the proposed method performs well.

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عنوان ژورنال:
  • Communications in Statistics - Simulation and Computation

دوره 42  شماره 

صفحات  -

تاریخ انتشار 2013