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Generalized quasi-linear mixed-effects model
Statistical Methods in Medical Research, 2022The generalized linear mixed model (GLMM) is one of the most common method in the analysis of longitudinal and clustered data in biological sciences. However, issues of model complexity and misspecification can occur when applying the GLMM. To address these issues, we extend the standard GLMM to a nonlinear mixed-effects model based on quasi-linear ...
Yusuke Saigusa +2 more
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Generalized Linear Mixed Models
2015This article provides an overview of generalized linear mixed models (GLMMs), how they are fit to data, and the inferences possible when using them. GLMMs are a class of statistical models that handle a wide variety of distributions for the outcome, accommodate nonlinear models, and model correlated data.
Fränzi Korner-Nievergelt +5 more
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Model comparison of generalized linear mixed models
Statistics in Medicine, 2005AbstractGeneralized linear mixed models (GLMMs) have been widely appreciated in biological and medical research. Maximum likelihood estimation has received a great deal of attention. Comparatively, not much has been done on model comparison or hypotheses testing.
Xin-Yuan, Song, Sik-Yum, Lee
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Generalized linear mixed models for meta-analysis
Statistics in Medicine, 1999We examine two strategies for meta-analysis of a series of 2 x 2 tables with the odds ratio modelled as a linear combination of study level covariates and random effects representing between-study variation. Penalized quasi-likelihood (PQL), an approximate inference technique for generalized linear mixed models, and a linear model fitted by weighted ...
R W, Platt, B G, Leroux, N, Breslow
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Linear Equality Constraints in the General Linear Mixed Model
Biometrics, 2001Scientists may wish to analyze correlated outcome data with constraints among the responses. For example, piecewise linear regression in a longitudinal data analysis can require use of a general linear mixed model combined with linear parameter constraints.
Edwards, Lloyd J. +3 more
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Generalized Linear Mixed Models
2017For analyzing repeated measures data, the necessity of considering the relationships between outcome variables as well as between outcome variables and explanatory variable are of concern. We have discussed about such models in previous chapters. All the models proposed in various chapters are fixed effect models. However, in some cases, the dependence
M. Ataharul Islam, Rafiqul I. Chowdhury
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Parsimonious Classification Via Generalized Linear Mixed Models
Journal of Classification, 2010zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Kauermann, G, Ormerod, J. T., Wand, M P
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Cook’s distance for generalized linear mixed models
Computational Statistics & Data Analysis, 2015zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Luis Gustavo B. Pinho +2 more
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The Generalized Linear Mixed Cluster-Weighted Model
Journal of Classification, 2015zbMATH Open Web Interface contents unavailable due to conflicting licenses.
INGRASSIA, Salvatore +3 more
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Bayesian Covariance Selection in Generalized Linear Mixed Models
Biometrics, 2005SummaryThe generalized linear mixed model (GLMM), which extends the generalized linear model (GLM) to incorporate random effects characterizing heterogeneity among subjects, is widely used in analyzing correlated and longitudinal data. Although there is often interest in identifying the subset of predictors that have random effects, random effects ...
Cai, Bo, Dunson, David B.
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