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Generalized Linear Mixed Model for Multivariate Multilevel Binomial Data
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 Title & Authors
Generalized Linear Mixed Model for Multivariate Multilevel Binomial Data
Lim, Hwa-Kyung; Song, Seuck-Heun; Song, Ju-Won; Cheon, Soo-Young;
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 Abstract
We are likely to face complex multivariate data which can be characterized by having a non-trivial correlation structure. For instance, omitted covariates may simultaneously affect more than one count in clustered data; hence, the modeling of the correlation structure is important for the efficiency of the estimator and the computation of correct standard errors, i.e., valid inference. A standard way to insert dependence among counts is to assume that they share some common unobservable variables. For this assumption, we fitted correlated random effect models considering multilevel model. Estimation was carried out by adopting the semiparametric approach through a finite mixture EM algorithm without parametric assumptions upon the random coefficients distribution.
 Keywords
GLMM;multi-level;correlated random effects;NPML;
 Language
Korean
 Cited by
1.
남아 출생률 자료에 대한 이질성 분석,임화경;송석헌;송주원;

응용통계연구, 2009. vol.22. 2, pp.365-373 crossref(new window)
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