Understanding correlates of child stunting in Ethiopia using generalized linear mixed models [PDF]
BMC Public Health, 2019 Background Stunting is an indicator of the devastating result of malnutrition in early childhood. The effects of childhood stunting are irreparable physical and cognitive harm.
Kasahun Takele +2 more
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Meta-analysis of binary outcomes via generalized linear mixed models: a simulation study [PDF]
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
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The R2D2 prior for generalized linear mixed models. [PDF]
Am Stat, 2021 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 +6 more sources
Generalized linear mixed models can detect unimodal species-environment relationships [PDF]
PeerJ, 2013 Niche theory predicts that species occurrence and abundance show non-linear, unimodal relationships with respect to environmental gradients. Unimodal models, such as the Gaussian (logistic) model, are however more difficult to fit to data than linear ...
Tahira Jamil, Cajo J.F. ter Braak
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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 +4 more
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Statistical Analysis of Zebrafish Locomotor Behaviour by Generalized Linear Mixed Models [PDF]
Scientific Reports, 2017 Upon a drastic change in environmental illumination, zebrafish larvae display a rapid locomotor response. This response can be simultaneously tracked from larvae arranged in multi-well plates.
Yiwen Liu +10 more
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Basic Features of the Analysis of Germination Data with Generalized Linear Mixed Models
Data, 2020 Germination data are discrete and binomial. Although analysis of variance (ANOVA) has long been used for the statistical analysis of these data, generalized linear mixed models (GzLMMs) provide a more consistent theoretical framework. GzLMMs are suitable
Alberto Gianinetti
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Bayesian inference for generalized linear mixed models [PDF]
Biostatistics, 2009 Generalized linear mixed models (GLMMs) continue to grow in popularity due to their ability to directly acknowledge multiple levels of dependency and model different data types. For small sample sizes especially, likelihood-based inference can be unreliable with variance components being particularly difficult to estimate.
Fong, Youyi +2 more
openaire +4 more sources
MCMC Methods for Multi-Response Generalized Linear Mixed Models: The MCMCglmm R Package [PDF]
Journal of Statistical Software, 2010 Generalized linear mixed models provide a flexible framework for modeling a range of data, although with non-Gaussian response variables the likelihood cannot be obtained in closed form.
Jarrod Had
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Efficient computation of high-dimensional penalized generalized linear mixed models by latent factor modeling of the random effects. [PDF]
BiometricsHeiling HM +5 more
europepmc +3 more sources