A brief introduction to mixed effects modelling and multi-model inference in ecology

The coefficient of determination R 2 and intra-class correlation coefficient from generalized linear mixed-effects models revisited and expanded

(2017) Shinichi Nakagawa et al.   Journal of the Royal Society Interface

Statistical Quantification of Individual Differences (SQuID): an educational and statistical tool for understanding multilevel phenotypic data in linear mixed models

(2016) Hassen Allegue et al.   Methods in Ecology and Evolution

The relative performance of AIC, AICC and BIC in the presence of unobserved heterogeneity

(2016) Mark J. Brewer et al.   Methods in Ecology and Evolution

A protocol for conducting and presenting results of regression-type analyses

(2016) Alain F. Zuur et al.   Methods in Ecology and Evolution

Three points to consider when choosing a LM or GLM test for count data

(2016) David I. Warton et al.   Methods in Ecology and Evolution

Ten Simple Rules for Effective Statistical Practice

(2016) Robert E. Kass et al.   PLoS Computational Biology

Multilevel analysis quantifies variation in the experimental effect while optimizing power and preventing false positives

(2015) Emmeke Aarts et al.   BMC NEUROSCIENCE

Model averaging and muddled multimodel inferences

(2015) Brian S. Cade   ECOLOGY

Fitting Linear Mixed-Effects Models Usinglme4

(2015) Douglas Bates et al.   Journal of Statistical Software

History of multimodel inference via model selection in wildlife science

(2015) Mark S. Lindberg et al.   JOURNAL OF WILDLIFE MANAGEMENT

MMI: Multimodel inference or models with management implications?

(2015) John Fieberg et al.   JOURNAL OF WILDLIFE MANAGEMENT

Truth, models, model sets, AIC, and multimodel inference: A Bayesian perspective

(2015) Richard J. Barker et al.   JOURNAL OF WILDLIFE MANAGEMENT

The fickle P value generates irreproducible results

(2015) Lewis G Halsey et al.   NATURE METHODS

Quantifying variable importance in a multimodel inference framework

(2015) Xingli Giam et al.   Methods in Ecology and Evolution

For testing the significance of regression coefficients, go ahead and log-transform count data

(2015) Anthony R. Ives   Methods in Ecology and Evolution

piecewiseSEM: Piecewise structural equation modelling inr for ecology, evolution, and systematics

(2015) Jonathan S. Lefcheck   Methods in Ecology and Evolution

A comparison of observation-level random effect and Beta-Binomial models for modelling overdispersion in Binomial data in ecology & evolution

(2015) Xavier A. Harrison   PeerJ

Testing environmental and genetic effects in the presence of spatial autocorrelation

(2014) François Rousset et al.   ECOGRAPHY

In defense ofPvalues

(2014) Paul A. Murtaugh   ECOLOGY

Rising complexity and falling explanatory power in ecology

(2014) Etienne Low-Décarie et al.   FRONTIERS IN ECOLOGY AND THE ENVIRONMENT

Generalized additive models for large data sets

(2014) Simon N. Wood et al.   JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES C-APPLIED STATISTICS

Extension of Nakagawa & Schielzeth'sR2GLMMto random slopes models

(2014) Paul C.D. Johnson   Methods in Ecology and Evolution

Ecologists overestimate the importance of predictor variables in model averaging: a plea for cautious interpretations

(2014) Matthias Galipaud et al.   Methods in Ecology and Evolution

Using observation-level random effects to model overdispersion in count data in ecology and evolution

(2014) Xavier A. Harrison   PeerJ

Random effects structure for confirmatory hypothesis testing: Keep it maximal

(2013) Dale J. Barr et al.   JOURNAL OF MEMORY AND LANGUAGE

Collinearity: a review of methods to deal with it and a simulation study evaluating their performance

(2012) Carsten F. Dormann et al.   ECOGRAPHY

Nested by design: model fitting and interpretation in a mixed model era

(2012) Holger Schielzeth et al.   Methods in Ecology and Evolution

A general and simple method for obtainingR2from generalized linear mixed-effects models

(2012) Shinichi Nakagawa et al.   Methods in Ecology and Evolution

Multimodel inference in ecology and evolution: challenges and solutions

(2011) C. E. GRUEBER et al.   JOURNAL OF EVOLUTIONARY BIOLOGY

Uninformative Parameters and Model Selection Using Akaike's Information Criterion

(2011) TODD W. ARNOLD   JOURNAL OF WILDLIFE MANAGEMENT

Issues in information theory-based statistical inference—a commentary from a frequentist’s perspective

(2010) Roger Mundry   BEHAVIORAL ECOLOGY AND SOCIOBIOLOGY

Using information theory as a substitute for stepwise regression in ecology and behavior

(2010) Gergely Hegyi et al.   BEHAVIORAL ECOLOGY AND SOCIOBIOLOGY

Model selection and model averaging in behavioural ecology: the utility of the IT-AIC framework

(2010) Shane A. Richards et al.   BEHAVIORAL ECOLOGY AND SOCIOBIOLOGY

AIC model selection and multimodel inference in behavioral ecology: some background, observations, and comparisons

(2010) Kenneth P. Burnham et al.   BEHAVIORAL ECOLOGY AND SOCIOBIOLOGY

Developing multiple hypotheses in behavioral ecology

(2010) Ned A. Dochtermann et al.   BEHAVIORAL ECOLOGY AND SOCIOBIOLOGY

Cryptic multiple hypotheses testing in linear models: overestimated effect sizes and the winner's curse

(2010) Wolfgang Forstmeier et al.   BEHAVIORAL ECOLOGY AND SOCIOBIOLOGY

Model averaging, missing data and multiple imputation: a case study for behavioural ecology

(2010) Shinichi Nakagawa et al.   BEHAVIORAL ECOLOGY AND SOCIOBIOLOGY

Dealing with collinearity in behavioural and ecological data: model averaging and the problems of measurement error

(2010) Robert P. Freckleton   BEHAVIORAL ECOLOGY AND SOCIOBIOLOGY

A brief guide to model selection, multimodel inference and model averaging in behavioural ecology using Akaike’s information criterion

(2010) Matthew R. E. Symonds et al.   BEHAVIORAL ECOLOGY AND SOCIOBIOLOGY

Repeatability for Gaussian and non-Gaussian data: a practical guide for biologists

(2010) Shinichi Nakagawa et al.   BIOLOGICAL REVIEWS

The arcsine is asinine: the analysis of proportions in ecology

(2010) David I. Warton et al.   ECOLOGY

Do not log-transform count data

(2010) Robert B. O’Hara et al.   Methods in Ecology and Evolution

Simple means to improve the interpretability of regression coefficients

(2010) Holger Schielzeth   Methods in Ecology and Evolution

Model selection bias and Freedman’s paradox

(2009) Paul M. Lukacs et al.   ANNALS OF THE INSTITUTE OF STATISTICAL MATHEMATICS

Performance of several variable-selection methods applied to real ecological data

(2009) Paul A. Murtaugh   ECOLOGY LETTERS

An ecologist’s guide to the animal model

(2009) Alastair J. Wilson et al.   JOURNAL OF ANIMAL ECOLOGY

New perspectives for estimating body condition from mass/length data: the scaled mass index as an alternative method

(2009) Jordi Peig et al.   OIKOS

Generalized linear mixed models: a practical guide for ecology and evolution

(2009) Benjamin M. Bolker et al.   TRENDS IN ECOLOGY & EVOLUTION

A protocol for data exploration to avoid common statistical problems

(2009) Alain F. Zuur et al.   Methods in Ecology and Evolution

A simple method for distinguishing within- versus between-subject effects using mixed models

(2008) Martijn van de Pol et al.   ANIMAL BEHAVIOUR

Conclusions beyond support: overconfident estimates in mixed models

(2008) H. Schielzeth et al.   BEHAVIORAL ECOLOGY

Missing inaction: the dangers of ignoring missing data

(2008) Shinichi Nakagawa et al.   TRENDS IN ECOLOGY & EVOLUTION

Scaling regression inputs by dividing by two standard deviations

(2007) Andrew Gelman   STATISTICS IN MEDICINE