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

By Benjamin M. Bolker, Mollie E. Brooks, C. Clark, S. Geange, J. Poulsen, M. Henry, H. Stevens, Jada White. Trends in Ecology & Evolution, 2009

8,548 citations recorded by the source corpus.

Subfields: Ecology, Evolution, Behavior and Systematics, Nature and Landscape Conservation

View Paper: https://www.semanticscholar.org/paper/9e9fea00e8adaaf2b658948e767b46a8ee2cd152

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In Ecology, Evolution, Behavior and Systematics

In Nature and Landscape Conservation

Citations in the corpus

Decision making in ant foragers (Lasius niger) facing conflicting private and social information (2011, methodology): “We included colony as a random effect to control for the non-independence of data points from the same colony (Bolker et al. 2009; Zuur et al. 2009).”
Extensive gaps and biases in our knowledge of a well‐known fauna: implications for integrating biological traits into macroecology (2012, neutral): “Note that our modelling approach is identical to that advocated by Bolker et al. (2009) as preliminary procedures to fitting GLMMs.”
Experimental evidence for stronger cacao yield limitation by pollination than by plant resources (2010, methodology): “We refer to Pinheiro and Bates (2000) and Bolker et al. (2009) for introductions to linear mixed models and GLMMs, respectively.”
Ecologists overestimate the importance of predictor variables in model averaging: a plea for cautious interpretations (2014, neutral): “…of models based on 95% cumulated model weights, (Burnham & Anderson 2002), the subset of models with Di lower than 2, 4, 6 and 10 (Richards 2008, Bolker et al. 2009), or a confidence 20 50 100 200 500 1000 2000 5000 0·0 0·2 0·4 0·6 0·8 1·0 (a) 20 50 100 200 500 1000 2000…”
Temperature‐driven shifts in a host‐parasite interaction drive nonlinear changes in disease risk (2012, methodology): “Following Bolker et al. (2009), GLMMs were fit using the Laplace approximation method using the lme4 package (lmer function) while the linear mixed effects analyses were performed using the nlme package (lme function) in R (R Development Core Team 2008).”
Cover Crop Biomass Production Is More Important than Diversity for Weed Suppression (2019, methodology): “To detect differences between midand end-season weed and cover crop biomass, composition, species diversity, and functional diversity, we conducted Type III ANOVA F tests on linear mixed effects regression models fitted with restricted maximum likelihood using Satterthwaite approximations for degree”
Ecological, social, and reproductive factors shape producer–scrounger dynamics in baboons (2009, methodology): “Because each foraging event involved a dyad comprising the focal animal and its nearest foraging neighbor, and both individuals could also appear in other dyads, we used cross-classified GLMMs (Bolker et al. 2009) implemented in MLwiN (Rasbash et al.”
Biodiversity consequences of land-use change and forest disturbance in the Amazon:a multi-scale assessment using ant communities (2016, methodology): “To assess the relationship between ant species richness and land-use class at the site scale, we used Generalized Linear Mixed Model (GLMM, Bolker et al. 2009) with land-use class as the explanatory variable and landscape identity as the random factor.”
Identification of 100 fundamental ecological questions (2013, methodology): “…rapid identification and even phylogeny building at the community level, the development of new statistical methods (e.g. mixed models and Bayesian statistics, e.g. Bolker et al. 2009), monitoring tools such as remote sensing (Asner et al. 2008) and geo-tagging of individuals (Block et al. 2001).”
The arcsine is asinine: the analysis of proportions in ecology. (2011, methodology): “More formal methods of assessing overdispersion are available (Collett 2002).”
The influence of landscape, patch, and within-patch factors on species presence and abundance: a review of focal patch studies (2010, methodology): “For statistical inference of fixed effects, we first fit a full model including all covariates, and then used a backward stepwise elimination procedure (P to remove \0.10, P to enter \0.05) based on Wald Ftests (Bolker et al. 2008).”
Conspecific and phylogenetic density‐dependent survival differs across life stages in a tropical forest (2015, methodology): “…effects on individual survival at multiple life-history stages, we used generalized linear mixed-effects models (GLMMs; Gelman & Pardoe 2006; Bolker et al. 2009) with binomial errors to model individual survival (lived/died) as a function of conspecific neighbour density, heterospecific…”