Power analysis
G* power for classical statistical models (t-test, ANOVA, regressions)
Faul, F., Erdfelder, E., Buchner, A., & Lang, A.-G. (2009). Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses. Behavior Research Methods, 41(4), 1149–1160. https://doi.org/10.3758/BRM.41.4.1149 Power analysis for mixed-effect models
Conceptual review
When you have simple experimental design
Westfall, J., Kenny, D. A., & Judd, C. M. (2014). Statistical power and optimal design in experiments in which samples of participants respond to samples of stimuli. Journal of Experimental Psychology: General, 143(5), 2020–2045. https://doi.org/10.1037/xge0000014 Introduction to simr: It is now possible to estimate power for more complex mixed effect models
Green, P., & MacLeod, C. J. (2016). SIMR: an R package for power analysis of generalized linear mixed models by simulation. Methods in Ecology and Evolution, 7(4), 493–498. https://doi.org/10.1111/2041-210X.12504 Some example analysis using simr
Brysbaert, M., & Stevens, M. (2018). Power Analysis and Effect Size in Mixed Effects Models: A Tutorial. Journal of Cognition, 1(1), 9. https://doi.org/10.5334/joc.10 Power analysis tutorial in details (based on actual dataset)
tutorial using simr in the latter part
Tutorial on simr (creating simulated dataset from scratch; specifying fixed and random effect parameters)