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
Citations
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Experimental heatwaves compromise sperm function and cause transgenerational damage in a model insect.
Kris Sales,Ramakrishnan Vasudeva,Matthew E. Dickinson,Joanne L. Godwin,Alyson J. Lumley,Łukasz Michalczyk,Laura Hebberecht,Paul Thomas,Aldina M. A. Franco,Matthew J. G. Gage +9 more
TL;DR: Simulated heatwaves harm male reproductive potential by reducing sperm number and viability, an effect which persisted into the next generation, providing one potential driver behind biodiversity declines and contractions through global warming.
Journal ArticleDOI
Cerebellar Contribution to Social Cognition
TL;DR: Patients with cerebellar damage were impaired on an EA task associated with deficient social skills and autism spectrum behaviors and experienced psychosocial difficulties on the CNRS, which has relevance for ataxias, the cerebellary cognitive affective/Schmahmann syndrome, and neuropsychiatric disorders with Cerebellar pathology.
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Root exudate cocktails: the link between plant diversity and soil microorganisms?
TL;DR: These findings provide the first experimental evidence that root exudate diversity is a crucial link between plant diversity and soil microorganisms.
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Multiple forest attributes underpin the supply of multiple ecosystem services
María R. Felipe-Lucia,Santiago Soliveres,Santiago Soliveres,Caterina Penone,Peter Manning,Fons van der Plas,Steffen Boch,Steffen Boch,Daniel Prati,Christian Ammer,Peter Schall,Martin M. Gossner,Martin M. Gossner,Jürgen Bauhus,François Buscot,Stefan Blaser,Stefan Blaser,Nico Blüthgen,Ángel de Frutos,Martin Ehbrecht,Kevin Frank,Kezia Goldmann,Falk Hänsel,Kirsten Jung,Tiemo Kahl,Thomas Nauss,Yvonne Oelmann,Rodica Pena,Andrea Polle,Swen C. Renner,Michael Schloter,Ingo Schöning,Marion Schrumpf,Ernst Detlef Schulze,Emily F. Solly,Emily F. Solly,Elisabeth Sorkau,Barbara Stempfhuber,Marco Tschapka,Marco Tschapka,Wolfgang W. Weisser,Tesfaye Wubet,Markus Fischer,Eric Allan +43 more
TL;DR: It is suggested that managing forests to increase structural heterogeneity, maintain large trees, and canopy gaps would promote the supply of multiple ecosystem services and suggest that a coordinated landscape-scale strategy could help to mitigate trade-offs in human-dominated landscapes.
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Prediction of enteric methane production, yield, and intensity in dairy cattle using an intercontinental database
M. Niu,Ermias Kebreab,Alexander N. Hristov,Joonpyo Oh,C. Arndt,André Bannink,Ali R. Bayat,Andre F. Brito,Tommy M. Boland,David P. Casper,Les A. Crompton,Jan Dijkstra,Maguy Eugène,Phil C. Garnsworthy,Najmul Haque,A.L.F. Hellwing,Pekka Huhtanen,Michael Kreuzer,B. Kuhla,Peter Lund,Jørgen Steen Madsen,Cécile Martin,Shelby C. McClelland,Mark McGee,Peter J. Moate,Stefan M. Muetzel,Camila Muñoz,Padraig O'Kiely,Nico Peiren,Christopher K. Reynolds,Angela Schwarm,K. J. Shingfield,T. M. Storlien,Martin Riis Weisbjerg,David R. Yáñez-Ruiz,Zhongtang Yu +35 more
TL;DR: Information on DMI is required for good prediction, and other factors such as dietary neutral detergent fiber (NDF) concentration, improve the prediction for enteric CH 4 yield and intensity prediction.
References
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TL;DR: Linear Mixed-Effects and Nonlinear Mixed-effects (NLME) models have been studied in the literature as mentioned in this paper, where the structure of grouped data has been used for fitting LME models.
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