Fitting Linear Mixed-Effects Models Using lme4
TLDR
In this article, a model is described in an lmer call by a formula, in this case including both fixed-and random-effects terms, and the formula and data together determine a numerical representation of the model from which the profiled deviance or the profeatured REML criterion can be evaluated as a function of some of model parameters.Abstract:
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 an lmer call by a formula, in this case including both fixed- and random-effects terms. The formula and data together determine a numerical representation of the model from which the profiled deviance or the profiled REML criterion can be evaluated as a function of some of the model parameters. The appropriate criterion is optimized, using one of the constrained optimization functions in R, to provide the parameter estimates. We describe the structure of the model, the steps in evaluating the profiled deviance or REML criterion, and the structure of classes or types that represents such a model. Sufficient detail is included to allow specialization of these structures by users who wish to write functions to fit specialized linear mixed models, such as models incorporating pedigrees or smoothing splines, that are not easily expressible in the formula language used by lmer.read more
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The CIRCORT database: Reference ranges and seasonal changes in diurnal salivary cortisol derived from a meta-dataset comprised of 15 field studies.
Robert Miller,Tobias Stalder,Marc N. Jarczok,David M. Almeida,Ellena Badrick,Meike Bartels,Dorret I. Boomsma,Christopher L. Coe,Marieke C. J. Dekker,Bonny Donzella,Joachim E. Fischer,Megan R. Gunnar,Meena Kumari,Florian Lederbogen,Christine Power,Carol D. Ryff,S.V. Subramanian,Henning Tiemeier,Sarah Enos Watamura,Clemens Kirschbaum +19 more
TL;DR: This integrative summary provides important reference values on salivary cortisol to aid basic scientists and clinicians in interpreting deviations from the normal diurnal cycle.
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Decomposing multiple dimensions of stability in global change experiments.
Helmut Hillebrand,Silke Langenheder,Karen Lebret,Eva S. Lindström,Örjan Östman,Maren Striebel +5 more
TL;DR: This work shows how the response to single perturbations can be decomposed in different stability aspects (resistance, resilience, recovery, temporal stability) for both ecosystem functions and community composition, and finds that extended community recovery is tightly connected to a nearly complete recovery of the function.
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R$^{2}$s for Correlated Data: Phylogenetic Models, LMMs, and GLMMs.
TL;DR: Symbol is an extension of the ordinary least‐squares R2 that weights residuals by variances and covariances estimated by the model; it is closely related to Symbol presented by Nakagawa and Schielzeth (2013), a general and simple method for obtaining R2 from generalized linear mixed‐effects models.
Journal ArticleDOI
An investigation into per- and polyfluoroalkyl substances (PFAS) in nineteen Australian wastewater treatment plants (WWTPs).
Timothy L. Coggan,Damien Moodie,Adam Kolobaric,Drew Szabo,Jeff Shimeta,Nicholas D. Crosbie,Nicholas D. Crosbie,Elliot Lee,Milena Fernandes,Bradley O Clarke +9 more
TL;DR: The compound 6:2 FTS was an important contributor to PFAS emissions in the studied Australian WWTPs, supporting the need for future research on its sources (including precursor degradation), environmental fate and impact in Australian aquatic environments receiving WWTP effluent.
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Gut Microbiota Modifies Olfactory-Guided Microbial Preferences and Foraging Decisions in Drosophila
Adam C. N. Wong,Qiao-Ping Wang,Juliano Morimoto,Juliano Morimoto,Alistair M. Senior,Alistair M. Senior,Mathieu Lihoreau,Mathieu Lihoreau,G. Gregory Neely,Stephen J. Simpson,Fleur Ponton,Fleur Ponton +11 more
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References
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