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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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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
2015AbstractGeneralized 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-effects models
2008Generalized 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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Organic mixed conductors for bioinspired electronics
Nature Reviews Materials, 2023Paschalis Gkoupidenis +2 more
exaly
Using Generalized Linear (Mixed) Models in HCI
2016In 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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