SIMR: an R package for power analysis of generalized linear mixed models by simulation

Fitting Linear Mixed-Effects Models Usinglme4

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

A Kenward-Roger Approximation and Parametric Bootstrap Methods for Tests in Linear Mixed Models - TheRPackagepbkrtest

(2015) Ulrich Halekoh et al.   Journal of Statistical Software

Power analysis for generalized linear mixed models in ecology and evolution

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

Empirical Power and Sample Size Calculations for Cluster-Randomized and Cluster-Randomized Crossover Studies

(2012) Nicholas G. Reich et al.   PLoS One

Simulation methods to estimate design power: an overview for applied research

(2011) Benjamin F Arnold et al.   BMC Medical Research Methodology

Monitoring temporal trends in spatially structured populations: how should sampling effort be allocated between space and time?

(2011) Jonathan R. Rhodes et al.   ECOGRAPHY

Measuring individual differences in reaction norms in field and experimental studies: a power analysis of random regression models

(2010) Julien G. A. Martin et al.   Methods in Ecology and Evolution

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

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

Size and power of tests for a zero random effect variance or polynomial regression in additive and linear mixed models

(2007) Fabian Scheipl et al.   COMPUTATIONAL STATISTICS & DATA ANALYSIS