Consider stratified data in which Y_{i1} ,..., Y_{in_i} denote real-valued response variables corresponding to the observations from stratum i, i = 1,..., m and suppose that Yij follows an exponential family distribution with canonical parameter of the form θ_{ij} = x_{ij}β + γ_i. In analyzing data of this type, the stratum-specific parameters are often modeled as random effects; a commonly-used approach is to assume that γ_1 ,..., γ_m are independent, identically distributed random variables. The purpose of this paper is to consider an alternative approach to defining the random effects, in which the stratum means of the response variable are assumed to be independent and identically distributed, with a distribution not depending on β. It ...
The goodness-of-fit of the distribution of random effects in a generalized linear mixed model is ass...
We consider the situation where the random effects in a generalized linear mixed model may be correl...
xthybrid estimates generalized linear mixed models that split the effects of cluster-varying covaria...
Consider stratified data in which Yi 1, ..., Yi ni denote real-valued response variables correspondi...
The Generalized Linear Mixed Model (GLMM) is a natural extension and mixture of a Linear Mixed Model...
Summary. The relationship between a primary endpoint and features of longitudinal profiles of a cont...
A standard assumption is that the random effects of Generalized Linear Mixed Effects Models (GLMMs) ...
International audienceIn this paper, an alternative estimation approach is proposed to fit linear mi...
We propose Bayesian generalized additive mixed models for correlated data, which arise frequently in...
Generalized additive mixed models extend the common parametric predictor of generalized linear model...
Non-Gaussian outcomes are often modeled using members of the so-called exponential family. Notorious...
International audienceAn alternative estimation approach is proposed to fit a linear mixed effects m...
This dissertation considers the problem of learning the underlying statistical structure of complex ...
Estimation in generalized linear mixed models (GLMMs) is often based on maximum likelihood theory, a...
AbstractBayesian inference methods are used extensively in the analysis of Generalized Linear Mixed ...
The goodness-of-fit of the distribution of random effects in a generalized linear mixed model is ass...
We consider the situation where the random effects in a generalized linear mixed model may be correl...
xthybrid estimates generalized linear mixed models that split the effects of cluster-varying covaria...
Consider stratified data in which Yi 1, ..., Yi ni denote real-valued response variables correspondi...
The Generalized Linear Mixed Model (GLMM) is a natural extension and mixture of a Linear Mixed Model...
Summary. The relationship between a primary endpoint and features of longitudinal profiles of a cont...
A standard assumption is that the random effects of Generalized Linear Mixed Effects Models (GLMMs) ...
International audienceIn this paper, an alternative estimation approach is proposed to fit linear mi...
We propose Bayesian generalized additive mixed models for correlated data, which arise frequently in...
Generalized additive mixed models extend the common parametric predictor of generalized linear model...
Non-Gaussian outcomes are often modeled using members of the so-called exponential family. Notorious...
International audienceAn alternative estimation approach is proposed to fit a linear mixed effects m...
This dissertation considers the problem of learning the underlying statistical structure of complex ...
Estimation in generalized linear mixed models (GLMMs) is often based on maximum likelihood theory, a...
AbstractBayesian inference methods are used extensively in the analysis of Generalized Linear Mixed ...
The goodness-of-fit of the distribution of random effects in a generalized linear mixed model is ass...
We consider the situation where the random effects in a generalized linear mixed model may be correl...
xthybrid estimates generalized linear mixed models that split the effects of cluster-varying covaria...