Generalized linear mixed-model (GLMM) trees: A flexible decision-tree method for multilevel and longitudinal datamultilevel datadecision makingdecision-tree methodsmixed-effects modelssubgroup detectionObjective: Decision-tree methods are machine-learning methods which provide results that are relatively easy...
Generalized linear mixed models (GLMMs) are widely used to analyse non-normal response data with extra-variation, but non-robust estimators are still routinely used. We propose robust methods for maximum quasi-likelihood and residual maximum quasi-likelihood estimation to limit the influence of ...
Generalized linear mixed models (GLMMs) are a class of models that incorporates random effects into the linear predictor of a generalized linear model (GLM). This allows the modeling of correlated data within the context of GLMs and greatly extends their breadth of applicability. They thus include...
Generalized linear mixed models (GLMMs) are commonly used to analyze longitudinal categorical data. In these models, we typically assume that the random ef... K Lee,JB Lee,J Hagan,... - 《Computational Statistics & Data Analysis》 被引量: 29发表: 2012年 Variance components analysis for pedig...
generalized linear mixed models:广义线性混合模型 下载积分: 2000 内容提示: Generalized Linear MixedModelsIntroductionGeneralized linear models (GLMs) represent a classof fixed effects regression models for several types ofdependent variables (i.e., continuous, dichotomous,counts). McCullagh and Nelder [...
U.K. Generalized linear mixed model So far we have allowed very flexible models for the expected response and very simplistic models for its stochastic component. Let’s fix that. A Generalized linear mixed model (GLMM) has the form g(µ i ) = X i β +Z i b, b ∼ N(0,...
GENERALIZED LINEAR MIXED MODELS The new GLIMMIX procedure fits generalized linear mixed models (GLMMs). Like linear mixed models fit by the MIXED procedure, GLMMs assume normal random effects. Conditional on these random effects, the data have a distribution in the exponential family. For example, ...
The generalized linear mixed models (GLMMs) for clustered data are studied when covariates are measured with error. The most conventional measurement error models are based on either linear mixed models (LMMs) or GLMMs. Even without the measurement error, the frequentist analysis of LMM, and partic...
Generalized linear mixed models (GLMMs) provide a more flexible approach for analyzing nonnormal data when random effects are present. The explosion of research on GLMMs in the last decade has generated considerable uncertainty for practitioners in ecology and evolution. Despite the availability of ...
1.Objective :To discussgeneralized linear mixed models(GLMMs) of categorical repeated measurement datas in clinical curative effect evaluation,implementing with GLIMMIX macro in SAS8.目的:探讨临床疗效评价中分类重复测量资料的广义线性混合效应模型(GLMMs)及SAS8。