Results 21 to 30 of about 574,217 (170)

Flexible Bayesian Dirichlet mixtures of generalized linear mixed models for count data

Scientific African, 2021
The need to model count data correctly calls for introducting a flexible yet robust model that can sufficiently handle various types of count data. Models such as Ordinary Least Squares (OLS) used in the past were considered unsuitable.
Olumide S. Adesina, Dawud A. Agunbiade, Pelumi E. Oguntunde   +2 more
doaj   +1 more source

Generalized fiducial inference for normal linear mixed models [PDF]

, 2012
While linear mixed modeling methods are foundational concepts introduced in any statistical education, adequate general methods for interval estimation involving models with more than a few variance components are lacking, especially in the unbalanced ...
Cisewski, Jessi, Hannig, Jan
core   +4 more sources

Bayesian multilevel modelling of the association between socio-economic status and stunting among under-five-year children in Tanzania

Journal of Health, Population and Nutrition, 2023
Background Stunting is associated with socioeconomic status (SES) which is multidimensional. This study aimed to compare different SES indices in predicting stunting.
Edwin Musheiguza, Tukae Mbegalo, Justine N. Mbukwa   +2 more
doaj   +1 more source

A vine copula mixed effect model for trivariate meta-analysis of diagnostic test accuracy studies accounting for disease prevalence [PDF]

, 2015
A bivariate copula mixed model has been recently proposed to synthesize diagnostic test accuracy studies and it has been shown that it is superior to the standard generalized linear mixed model in this context.
Aas K, Aristidis K Nikoloulopoulos, Brenner H, Chu H, Chu H, Demidenko E, Genest C, Genest C, Genest C, Hamza TH, Hoyer A, Hua L, Hult H, Joe H, Joe H, Joe H, Joe H, Joe H, Karageorgopoulos DE, Kurowicka D, Kuss O, Leeflang MMG, Leeflang MMG, Ma X, Mavridis D, McNeil AJ, Nash JC, Nelsen RB, Nikoloulopoulos AK, Nikoloulopoulos AK, Nikoloulopoulos AK, Nikoloulopoulos AK, Nikoloulopoulos AK, Nikoloulopoulos AK, Nikoloulopoulos AK, Panagiotelis A, Paul M, Serfling RJ, Shen C, Stroud AH, Vuong QH, Ye Y   +41 more
core   +2 more sources

Bayesian Model Selection for Generalized Linear Mixed Models

Biometrics, 2023
AbstractWe propose a Bayesian model selection approach for generalized linear mixed models (GLMMs). We consider covariance structures for the random effects that are widely used in areas such as longitudinal studies, genome-wide association studies, and spatial statistics.
Shuangshuang Xu, Marco A. R. Ferreira, Erica M. Porter, Christopher T. Franck   +3 more
openaire   +3 more sources

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, Nicole Trevisani, Marcio dos Santos, Altamir Frederico Guidolin, Jefferson Luís Meirelles Coimbra   +4 more
doaj   +1 more source

General Design Bayesian Generalized Linear Mixed Models

Statistical Science, 2006
Published at http://dx.doi.org/10.1214/088342306000000015 in the Statistical Science (http://www.imstat.org/sts/) by the Institute of Mathematical Statistics (http://www.imstat.org)
Zhao, Yihua, Staudenmayer, John, Coull, Brent, Wand, M.   +3 more
openaire   +4 more sources

Zero-Inflated Generalized Linear Mixed Models: A Better Way to Understand Data Relationships

Mathematics, 2021
Our article explores an underused mathematical analytical methodology in the social sciences. In addition to describing the method and its advantages, we extend a previously reported application of mixed models in a well-known database about corruption ...
Luiz Paulo Fávero, Joseph F. Hair, Rafael de Freitas Souza, Matheus Albergaria, Talles V. Brugni   +4 more
doaj   +1 more source

The R2D2 prior for generalized linear mixed models. [PDF]

Am Stat
In Bayesian analysis, the selection of a prior distribution is typically done by considering each parameter in the model. While this can be convenient, in many scenarios it may be desirable to place a prior on a summary measure of the model instead.
Yanchenko E, Bondell HD, Reich BJ.
europepmc   +4 more sources

To transform or not to transform: using generalized linear mixed models to analyse reaction time data. [PDF]

Front Psychol, 2015
Lo S, Andrews S.
europepmc   +2 more sources