Methodological implementation of mixed linear models in multi-locus genome-wide association studies [PDF]
Brief Bioinform, 2017 &NA; The mixed linear model has been widely used in genome‐wide association studies (GWAS), but its application to multi‐locus GWAS analysis has not been explored and assessed.
Y. Wen +9 more
semanticscholar +4 more sources
The Gut Microbial Architecture of Efficiency Traits in the Domestic Poultry Model Species Japanese Quail (Coturnix japonica) Assessed by Mixed Linear Models [PDF]
G3 (Bethesda), 2020 It is well known that mammals and avian gut microbiota compositions are shaped by the host genomes and affect quantitative traits. The microbial architecture describes the impact of the microbiota composition on quantitative trait variation and the ...
S. Vollmar +5 more
semanticscholar +2 more sources
Fitting Linear Mixed-Effects Models Using lme4 [PDF]
Journal of Statistical Software, 2015 Maximum likelihood or restricted maximum likelihood (REML) estimates of the parameters in linear mixed-effects models can be determined using the lmer function in the lme4 package for R. As for most model-fitting functions in R, the model is described in
Douglas Bates +3 more
doaj +2 more sources
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
doaj +3 more sources
lmerTest Package: Tests in Linear Mixed Effects Models
Journal of Statistical Software, 2017 One of the frequent questions by users of the mixed model function lmer of the lme4 package has been: How can I get p values for the F and t tests for objects returned by lmer?
Alexandra Kuznetsova +2 more
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On non-negative estimation of variance components in mixed linear models [PDF]
Journal of Advanced Research, 2016 Alternative estimators have been derived for estimating the variance components according to Iterative Almost Unbiased Estimation (IAUE). As a result two modified IAUEs are introduced.
Heba A. El Leithy +2 more
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Robustness of linear mixed‐effects models to violations of distributional assumptions
Methods in Ecology and Evolution, 2020 Linear mixed‐effects models are powerful tools for analysing complex datasets with repeated or clustered observations, a common data structure in ecology and evolution. Mixed‐effects models involve complex fitting procedures and make several assumptions,
Holger Schielzeth +2 more
exaly +2 more sources
A general and simple method for obtaining R 2 from generalized linear mixed‐effects models
Methods in Ecology and Evolution, 2013 Shinichi Nakagawa, Holger Schielzeth
exaly +2 more sources
LinDA: linear models for differential abundance analysis of microbiome compositional data [PDF]
Genome Biology, 2021 Differential abundance analysis is at the core of statistical analysis of microbiome data. The compositional nature of microbiome sequencing data makes false positive control challenging. Here, we show that the compositional effects can be addressed by a
Huijuan Zhou +3 more
semanticscholar +1 more source
BLMM: Parallelised computing for big linear mixed models
NeuroImage, 2022 Within neuroimaging large-scale, shared datasets are becoming increasingly commonplace, challenging existing tools both in terms of overall scale and complexity of the study designs.
Thomas Maullin-Sapey, Thomas E. Nichols
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