Generalized linear mixed-effects models

Results 21 to 30 of about 18,910,981 (254)

Finite Mixtures of Generalized Linear Regression Models [PDF]

, 2007
Generalized linear models have become a standard technique in the statistical modelling toolbox for investigating relationships between variables.
Bettina Grün +3 more
core +1 more source

Comparative study of diagnostic methods for linear mixed models and generalized linear models.

, 2022
graficas, tablasMuchos fenómenos de la naturaleza pueden ser representados por medio de modelos estadísticos de forma satisfactoria y, para validar estos modelos, los métodos de diagnóstico resultan ser herramientas muy útiles para la verificación de ...
Morales Foronda, Andrés Felipe
core +1 more source

Inference in skew generalized t-link models for clustered binary outcome via a parameter-expanded EM algorithm.

PLoS ONE, 2021
Binary Generalized Linear Mixed Model (GLMM) is the most common method used by researchers to analyze clustered binary data in biological and social sciences.
Chénangnon Frédéric Tovissodé, Aliou Diop, Romain Glèlè Kakaï +2 more
doaj +1 more source

Meta-analysis of binary outcomes via generalized linear mixed models: a simulation study

BMC Medical Research Methodology, 2018
Background Systematic reviews and meta-analyses of binary outcomes are widespread in all areas of application. The odds ratio, in particular, is by far the most popular effect measure.
Ilyas Bakbergenuly, Elena Kulinskaya
doaj +1 more source

Statistical model assumptions achieved by linear models: classics and generalized mixed

Revista Ciência Agronômica, 2020
When an agricultural experiment is completed and the data about the response variable is available, it is necessary to perform an analysis of variance.
Rita Carolina de Melo +4 more
doaj +1 more source

Flexible semiparametric mixed models [PDF]

, 2005
In linear mixed models the influence of covariates is restricted to a strictly parametric form. With the rise of semi- and nonparametric regression also the mixed model has been expanded to allow for additive predictors.
Reithinger, Florian, Tutz, Gerhard
core +1 more source

Modelos de predição para sobrevivência de plantas de Eucalyptus grandis Prediction models of Eucalyptus grandis plant survival

Ciência e Agrotecnologia, 2009
Objetivou-se com este trabalho comparar modelos de predição de plantas sobreviventes de Eucalyptus grandis. Utilizaram-se os seguintes modelos: modelo linear misto com os dados transformados, utilizando-se as transformações angular e BOX-COX; modelo ...
Telde Natel Custódio, Décio Barbin
doaj +1 more source

An Efficient Technique for Bayesian Modelling of Family Data Using the BUGS software

Frontiers in Genetics, 2014
Linear mixed models have become a popular tool to analyze continuous data from family-based designs by using random effects that model the correlation of subjects from the same family.
Harold T Bae, Thomas T Perls, Paola eSebastiani +2 more
doaj +1 more source

Social Functioning Within the First Years After Pediatric Brain Tumor Diagnosis and the Relationship With Family Psychosocial Risk

Pediatric Blood &Cancer, EarlyView.
ABSTRACT Background Survivors of pediatric brain tumors (PBTs) can experience long‐term social difficulties, impacting quality of life. Beyond medical and environmental factors, family psychosocial risk may play a role in social outcomes by shaping the caregiving environment and may provide intervention options.
Renske H. Houben +4 more
wiley +1 more source

Structural insights into an engineered feruloyl esterase with improved MHET degrading properties

FEBS Letters, EarlyView.
A feruloyl esterase was engineered to mimic key features of MHETase, enhancing the degradation of PET oligomers. Structural and computational analysis reveal how a point mutation stabilizes the active site and reshapes the binding cleft, expading substrate scope.
Panagiota Karampa +5 more
wiley +1 more source

random effects
generalized linear mixed models