lmerTest: Tests for random and fixed effects for linear mixed effect models (lmer objects of lme4 package)

By Alexandra Kuznetsova, Per Bruun Brockhoff, R. H. Christensen, R. Christensen, T. A. Kuznetsova, R. Christensen. 2014

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Long‐Term Studies Contribute Disproportionately to Ecology and Policy (2017, unknown): “org March 2017 / Vol. 67 No. 3 • BioScience 273 mechanisms underpinning those relationships (e.g., competition, life-history traits, functional complementarity, and redundancy) were revealed by long-term manipulations and monitoring of a temperate grassland ecosystem at the Cedar Creek Ecosystem Sci”
Light and growth in marine phytoplankton: allometric, taxonomic, and environmental variation (2015, methodology): “…on the focal traits using mixed models that included environment (coastal vs. oceanic) as a fixed effect, taxon as a random effect, an interaction between environment and taxon as a random effect, daylength and temperature as continuous predictors, and species and publication as random effects.”
Precision and accuracy in quantifying herbivory (2016, methodology): “Using the two response variables, we performed mixed model analysis of variance (anova) using the lme4 (Bates et al., 2014) and lmerTest (Kuznetsova et al., 2014) packages in R version 3.02 (R Core Team, 2013). lmerTest uses the algorithms of SAS Proc Mixed (Littell et al., 1996) to determine the…”
Evaluating significance in linear mixed-effects models in R (2016, methodology): “Both lmerTest (Kuznetsova et al., 2014) and afex (Singmann et al., 2015) have an anova function which can be used to provide p -values for each factor, calculated from the F statistic.”