This working paper has a twofold goal. On one hand, it provides a recap of Linear Mixed Models (LMMs): far from trying to be exhaustive, this rst part of the working paper focusses on the derivation of theoretical results on estimation of LMMs that are scattered in the literature or whose mathematical derivation is sometimes missing or too quickly sketched. On the other hand, it discusses various denitions that are available in the literature for the hat-matrix of Linear Mixed Models, showing their limitations and proving their equivalence
Beginning with the classical Gauss-Markov Linear Model for mixed effects and using the technique of ...
In this paper, a linear mixed model which has two random effects is broken up into two models. This ...
Linear mixed models are useful in biology, genetics, medical research, agriculture, industry, and ma...
This working paper has a twofold goal. On one hand, it provides a recap of Linear Mixed Models (LMM...
The book is based on several years of experience of both authors in teaching linear models at variou...
This paper presents and extends the concept of recursive residuals and their estimation to an import...
This paper presents recursive residuals de_nition, formulae and application to Linear Mixed Models (...
summary:In this paper, we consider a comparison problem of predictors in the context of linear mixed...
These are (incomplete) course notes about generalised linear mixed models (GLMM). Special emphasis i...
AbstractThe mixed model of analysis of variance is a linear model in which some terms that would oth...
Simplifying the often confusing array of software programs for fitting linear mixed models (LMMs), L...
This book covers two major classes of mixed effects models, linear mixed models and generalized line...
This is a companion volume to Plane Answers to Complex Questions: The Theory 0/ Linear Models. It co...
AbstractThe paper reviews the linear mixed model with a focus on parameter estimation and inference....
(from the chapter) This chapter presents a method based on a structural equation modeling (SEM) fram...
Beginning with the classical Gauss-Markov Linear Model for mixed effects and using the technique of ...
In this paper, a linear mixed model which has two random effects is broken up into two models. This ...
Linear mixed models are useful in biology, genetics, medical research, agriculture, industry, and ma...
This working paper has a twofold goal. On one hand, it provides a recap of Linear Mixed Models (LMM...
The book is based on several years of experience of both authors in teaching linear models at variou...
This paper presents and extends the concept of recursive residuals and their estimation to an import...
This paper presents recursive residuals de_nition, formulae and application to Linear Mixed Models (...
summary:In this paper, we consider a comparison problem of predictors in the context of linear mixed...
These are (incomplete) course notes about generalised linear mixed models (GLMM). Special emphasis i...
AbstractThe mixed model of analysis of variance is a linear model in which some terms that would oth...
Simplifying the often confusing array of software programs for fitting linear mixed models (LMMs), L...
This book covers two major classes of mixed effects models, linear mixed models and generalized line...
This is a companion volume to Plane Answers to Complex Questions: The Theory 0/ Linear Models. It co...
AbstractThe paper reviews the linear mixed model with a focus on parameter estimation and inference....
(from the chapter) This chapter presents a method based on a structural equation modeling (SEM) fram...
Beginning with the classical Gauss-Markov Linear Model for mixed effects and using the technique of ...
In this paper, a linear mixed model which has two random effects is broken up into two models. This ...
Linear mixed models are useful in biology, genetics, medical research, agriculture, industry, and ma...