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Linear Mixed Models: Gum and Beyond
Measurement Science Review, 2014 In Annex H.5, the Guide to the Evaluation of Uncertainty in Measurement (GUM) [1] recognizes the necessity to analyze certain types of experiments by applying random effects ANOVA models.
Arendacká Barbora +4 more
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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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Model Selection in Linear Mixed Models
Statistical Science, 2013 Linear mixed effects models are highly flexible in handling a broad range of data types and are therefore widely used in applications. A key part in the analysis of data is model selection, which often aims to choose a parsimonious model with other desirable properties from a possibly very large set of candidate statistical models.
Müller, Samuel +2 more
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Flexible semiparametric mixed models [PDF]
, 2005 In linear mixed models the influence of covariates is restricted to a strictly parametric form. With the rise of semi- and nonparametric regression also the mixed model has been expanded to allow for additive predictors.
Reithinger, Florian, Tutz, Gerhard
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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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Modified BIC Criterion for Model Selection in Linear Mixed Models
Mathematics, 2023 Linear mixed-effects models are widely used in applications to analyze clustered, hierarchical, and longitudinal data. Model selection in linear mixed models is more challenging than that of linear models as the parameter vector in a linear mixed model ...
Hang Lai, Xin Gao
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Restricted Likelihood Ratio Testing in Linear Mixed Models with General Error Covariance Structure [PDF]
, 2011 We consider the problem of testing for zero variance components in linear mixed models with correlated or heteroscedastic errors. In the case of independent and identically distributed errors, a valid test exists, which is based on the exact finite ...
Sonja Greven +5 more
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Frontiers in Psychology, 2017 We investigated the effects of violations of the sphericity assumption on Type I error rates for different methodical approaches of repeated measures analysis using a simulation approach.
Nicolas Haverkamp, André Beauducel
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Accessible analysis of longitudinal data with linear mixed effects models
Disease Models & Mechanisms, 2022 Longitudinal studies are commonly used to examine possible causal factors associated with human health and disease. However, the statistical models, such as two-way ANOVA, often applied in these studies do not appropriately model the experimental design,
Jessica I. Murphy +2 more
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Simple reparameterization to improve convergence in linear mixed models
Acta Agriculturae Slovenica, 2010 Slow convergence and mixing are one of the main problems of Markov chain Monte Carlo (McMC) algorithms applied to mixed models in animal breeding. Poor convergence is to a large extent caused by high posterior correlation between variance components and ...
Gregor GORJANC +3 more
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