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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Trait emotional intelligence and emotional experiences during the COVID-19 pandemic outbreak in Poland: A daily diary study.
TL;DR: The protective role of trait emotional intelligence during the COVID-19 pandemic outbreak was mainly associated with experiencing negative emotions less intensely, but not less frequently, while negatively with baseline negative affect and negative intensity.
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Agriculture and climate change are reshaping insect biodiversity worldwide
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Why do we lose protected areas? Factors influencing protected area downgrading, downsizing and degazettement in the tropics and subtropics.
TL;DR: A need is suggested for conservation practitioners to better consider PA characteristics, as well as the social, economic and political context in which PAs are situated, to aid the creation of more efficient and sustainable PA networks.
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Seasonal drivers of understorey temperature buffering in temperate deciduous forests across Europe
Florian Zellweger,Florian Zellweger,David A. Coomes,Jonathan Lenoir,Leen Depauw,Sybryn L. Maes,Monika Wulf,Keith Kirby,Jörg Brunet,Martin Kopecký,Martin Kopecký,František Máliš,Wolfgang Schmidt,Steffi Heinrichs,Jan den Ouden,Bogdan Jaroszewicz,Gauthier Buyse,Fabien Spicher,Kris Verheyen,Pieter De Frenne +19 more
TL;DR: Forest organisms experience less severe temperature extremes than suggested by currently available macro climate data; therefore, climate–species relationships and the responses of species to anthropogenic global warming cannot be modelled accurately in forests using macroclimate data alone.
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Soilborne fungi have host affinity and host-specific effects on seed germination and survival in a lowland tropical forest
Carolina Sarmiento,Paul Camilo Zalamea,James W. Dalling,James W. Dalling,Adam S. Davis,Simon Maccracken Stump,Jana M. U'Ren,A. Elizabeth Arnold +7 more
TL;DR: It is shown that communities of seed-associated fungi are structured more by plant species than by soil type, forest characteristics, or time in soil, which implicates them directly in the processes that have emerged as critical for diversity maintenance in species-rich tropical forests.
References
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TL;DR: Copyright (©) 1999–2012 R Foundation for Statistical Computing; permission is granted to make and distribute verbatim copies of this manual provided the copyright notice and permission notice are preserved on all copies.
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TL;DR: Detailed notes on Bayesian Computation Basics of Markov Chain Simulation, Regression Models, and Asymptotic Theorems are provided.
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Mixed-Effects Models in S and S-PLUS
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.
Book
Data Analysis Using Regression and Multilevel/Hierarchical Models
Andrew Gelman,Yu-Sung Su +1 more
TL;DR: Data Analysis Using Regression and Multilevel/Hierarchical Models is a comprehensive manual for the applied researcher who wants to perform data analysis using linear and nonlinear regression and multilevel models.