This thesis compares GAMs and GLMMs in the context of modeling nonlinear curves. The study contains a comprehensive simulation and a few real life data analyses. The simulation uses thousands of generated datasets to compare and contrast the two models' (and linear models as a benchmark) fit, extent of nonlinearity, and shape of the resulting curve. The data analyses extend the results of the simulation to GLMM/GAM curves of lung function with measures of smoking as the independent variable. An additional and larger real life data analysis with dichotomous outcomes rounds out the study and allow for more representative results.Cette these compare des GAM et GLMM dans le cadre de la modélisation des courbes non-linéaires. L'étude comprend un...
Multivariate Generalized Linear Mixed Models Using R presents robust and methodologically sound mode...
This book is about learning from data using the Generalized Additive Models for Location, Scale and ...
A generalized linear mixed model with a nonparametric distribution for the random effect is proposed...
In statistics, linear modelling techniques are widely used methods to explain one variable by others...
The Generalized Additive model (GAM) has been used as a standard tool for epidemiologic analysis exp...
Main Purpose The study is primarily a contribution to a question of strategy rather than the devel...
The generalized linear mixed model (GLMM) generalizes the standard linear model in three ways: accom...
Abstract. A nonparametric smoothing method for assessing the adequacy of generalized linear mixed mo...
In general, real life’s effects are not linear. To identify and interpret better the phenomena of ...
SCDs assess intervention effects by measuring units repeatedly over time in both the presence and th...
Šajā darbā aprakstītas divas matemātiskās modelēšanas metodes, tās ir, vispārinātais lineārais model...
In this thesis we describe the theory of generalized linear models and demon- strate its application...
The generalized additive models (GAM) is an extension of the usual linear regression by generalizing...
This talk will introduce the gnm package which provides functions for the specification, estimation ...
A new class of models, generalized additive mixed models (GAMMs), are proposed for analyzing correla...
Multivariate Generalized Linear Mixed Models Using R presents robust and methodologically sound mode...
This book is about learning from data using the Generalized Additive Models for Location, Scale and ...
A generalized linear mixed model with a nonparametric distribution for the random effect is proposed...
In statistics, linear modelling techniques are widely used methods to explain one variable by others...
The Generalized Additive model (GAM) has been used as a standard tool for epidemiologic analysis exp...
Main Purpose The study is primarily a contribution to a question of strategy rather than the devel...
The generalized linear mixed model (GLMM) generalizes the standard linear model in three ways: accom...
Abstract. A nonparametric smoothing method for assessing the adequacy of generalized linear mixed mo...
In general, real life’s effects are not linear. To identify and interpret better the phenomena of ...
SCDs assess intervention effects by measuring units repeatedly over time in both the presence and th...
Šajā darbā aprakstītas divas matemātiskās modelēšanas metodes, tās ir, vispārinātais lineārais model...
In this thesis we describe the theory of generalized linear models and demon- strate its application...
The generalized additive models (GAM) is an extension of the usual linear regression by generalizing...
This talk will introduce the gnm package which provides functions for the specification, estimation ...
A new class of models, generalized additive mixed models (GAMMs), are proposed for analyzing correla...
Multivariate Generalized Linear Mixed Models Using R presents robust and methodologically sound mode...
This book is about learning from data using the Generalized Additive Models for Location, Scale and ...
A generalized linear mixed model with a nonparametric distribution for the random effect is proposed...