Results 131 to 140 of about 570,704 (178)

Parsimonious Classification Via Generalized Linear Mixed Models

Journal of Classification, 2010
zbMATH 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, 2015
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Luis Gustavo B. Pinho, Juvêncio S. Nobre, Julio M. Singer   +2 more
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The Generalized Linear Mixed Cluster-Weighted Model

Journal of Classification, 2015
zbMATH Open Web Interface contents unavailable due to conflicting licenses.
INGRASSIA, Salvatore, PUNZO, ANTONIO, Vittadini G., Minotti S. C.   +3 more
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Bayesian Covariance Selection in Generalized Linear Mixed Models

Biometrics, 2005
SummaryThe 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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Generalized, Linear, and Mixed Models

Journal of the American Statistical Association, 2006
(2006). Generalized, Linear, and Mixed Models. Journal of the American Statistical Association: Vol. 101, No. 476, pp. 1724-1724.
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Linear and generalized linear mixed models

2015
AbstractGeneralized linear mixed models (GLMMs) are a powerful class of statistical models that combine the characteristics of generalized linear models and mixed models (models with both fixed and random predictor variables). This chapter: reviews the conceptual and theoretical background of GLMMs, focusing on the definition and meaning of random ...
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Generalized linear mixed models

2023
Luiz Paulo Fávero, Patrícia Belfiore, Rafael de Freitas Souza   +2 more
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Generalized linear mixed-effects models

2008
Generalized linear mixed-effects models, more commonly known as generalized linear mixed models, are very popular in longitudinal data analysis. They are a natural combination of two modeling strands, linear mixed models and generalized linear models.
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Generalized Linear Mixed Models

2021
Razia Azen, Cindy M. Walker
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Using Generalized Linear (Mixed) Models in HCI

2016
In HCI we often encounter dependent variables which are not (conditionally) normally distributed: we measure response-times, mouse-clicks, or the number of dialog steps it took a user to complete a task. Furthermore, we often encounter nested or grouped data; users are grouped within companies or institutes, or we obtain multiple observations within ...
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