Results 71 to 80 of about 570,704 (178)

Nonlocal priors for Bayesian variable selection in generalized linear models and generalized linear mixed models and their applications in biology data [PDF]

from short.pdf file.Dissertation supervisors: Dr. Marco A. R. Ferreira and Dr. Tieming Ji.Includes vita.A crucial problem in building a generalized linear model (GLM) or a generalized linear mixed model (GLMM) is to identify which subset of predictors ...
Wu, Ho-Hsiang, 1984-
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A Hybrid Bayesian Laplacian Approach for Generalized Linear Mixed Models [PDF]

, 2011
The analytical intractability of generalized linear mixed models (GLMMs) has generated a lot of research in the past two decades. Applied statisticians routinely face the frustrating prospect of widely disparate results produced by the methods that are ...
Begg, Colin B, Capanu, Marinela, Gonen, Mithat   +2 more
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Modeling Linguistic Variables With Regression Models: Addressing Non-Gaussian Distributions, Non-independent Observations, and Non-linear Predictors With Random Effects and Generalized Additive Models for Location, Scale, and Shape

Frontiers in Psychology, 2018
As statistical approaches are getting increasingly used in linguistics, attention must be paid to the choice of methods and algorithms used. This is especially true since they require assumptions to be satisfied to provide valid results, and because ...
Christophe Coupé
doaj   +1 more source

Review of Generalized Latent Variable Modeling by Skrondal and Rabe-Hesketh [PDF]

The new book by Skrondal and Rabe-Hesketh (2004) is reviewed.GLLAMM, generalized linear latent and mixed models, latent ...
Roger Newson
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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

ASSESSING GENERALIZED LINEAR MIXED MODELS USING RESIDUAL ANALYSIS [PDF]

[[abstract]]A nonparametric smoothing method for assessing the adequacy of generalized linear mixed models (GLMMs) is developed. The proposed method is based on smoothing the residuals over continuous covariates to avoid the partition of continuous ...
Lin, Kuo-Chin
core  

On Combining Exact and Approximative Proceedings for Testing Problems in Unbalanced Mixed Linear Models [PDF]

, 2000
A method for constructing approximative tests for arbitrary linear hypotheses on variance components in unbalanced mixed linear models is derived. The idea of cell mean models is used to derive independent and 2-distributed mean squares.
Weimann, Boris
core   +1 more source

Longitudinal method comparison: modeling polygenic risk for post-traumatic stress disorder over time in individuals of African and European ancestry

Frontiers in Genetics
Cross-sectional data allow the investigation of how genetics influence health at a single time point, but to understand how the genome impacts phenotype development, one must use repeated measures data.
Kristin Passero, Jennie G. Noll, Shefali Setia Verma, Claire Selin, Molly A. Hall   +4 more
doaj   +1 more source

Robust Estimation in Generalized Linear Mixed Models

Journal of the Royal Statistical Society Series B: Statistical Methodology, 2002
SummaryGeneralized 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 outlying observations in GLMMs.
Yau, Kelvin K. W., Kuk, Anthony Y. C.
openaire   +1 more source

glmmPen: High Dimensional Penalized Generalized Linear Mixed Models. [PDF]

R J, 2023
Heiling HM, Rashid NU, Li Q, Ibrahim JG.
europepmc   +1 more source