partR2: partitioning R2 in generalized linear mixed models [PDF]
PeerJ, 2021 The coefficient of determination R2 quantifies the amount of variance explained by regression coefficients in a linear model. It can be seen as the fixed-effects complement to the repeatability R (intra-class correlation) for the variance explained by ...
Martin A. Stoffel +2 more
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Federated generalized linear mixed models for collaborative genome-wide association studies [PDF]
iScience, 2023 Summary: Federated association testing is a powerful approach to conduct large-scale association studies where sites share intermediate statistics through a central server. There are, however, several standing challenges.
Wentao Li +3 more
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Neighborhood-level heterogeneity in childhood morbidity through generalized linear mixed models [PDF]
Frontiers in Public HealthObjectiveChildhood morbidities are crucial for improving long-term public health outcomes. This study aimed to examine the existence of child-specific and regional variation in childhood morbidity based on the cross-cutting study of the Performance ...
Endeshaw A. Derso +8 more
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The use of generalized linear mixed models to investigate postmortem lipids in textiles [PDF]
iScience, 2023 Summary: Human remains are oftentimes located with textile materials, making them a ubiquitous source of physical evidence. Human remains are also frequently discovered in outdoor environments, increasing the exposure to scavenging activity and soft ...
Sharni Collins +4 more
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Report Quality of Generalized Linear Mixed Models in Psychology: A Systematic Review [PDF]
Frontiers in Psychology, 2021 Generalized linear mixed models (GLMMs) estimate fixed and random effects and are especially useful when the dependent variable is binary, ordinal, count or quantitative but not normally distributed.
Roser Bono +3 more
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Modeling Multiple Item Context Effects With Generalized Linear Mixed Models [PDF]
Frontiers in Psychology, 2019 Item context effects refer to the impact of features of a test on an examinee's item responses. These effects cannot be explained by the abilities measured by the test. Investigations typically focus on only a single type of item context effects, such as
Norman Rose +6 more
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Inference of differentially expressed genes using generalized linear mixed models in a pairwise fashion [PDF]
PeerJ, 2023 Background Technological advances involving RNA-Seq and Bioinformatics allow quantifying the transcriptional levels of genes in cells, tissues, and cell lines, permitting the identification of Differentially Expressed Genes (DEGs).
Douglas Terra Machado +4 more
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Bayesian compositional generalized linear mixed models for disease prediction using microbiome data [PDF]
BMC BioinformaticsThe primary goal of predictive modeling for compositional microbiome data is to better understand and predict disease susceptibility based on the relative abundance of microbial species.
Li Zhang +5 more
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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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