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Data simulation with {faux} for mixed designs
Being able to simulate data allows you to prep analysis scripts for pre-registration, calculate power and sensitivity for analyses that don’t have empirical methods, create reproducible examples when your data are too big or confidential to share, enhance your understanding of statistical concepts, and create demo data for teaching and tutorials. In this talk, I will introduce the basics of simulation using the R package {faux}. We will focus on simulating data from a mixed design where trials are crossed with subjects, analysing this using {lme4}, understanding how the simulation parameters correspond to the output, and using simulation to calculate power.
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