The statistical power of a research design is closely linked to the reliability and replicability of empirical findings. Accounting for power while planning a study is therefore crucial and often a requirement for submissions in scientific journals. However, this can quickly become highly difficult in practice – especially for more complex, but very popular analysis procedures like linear mixed models (LMMs). In this workshop, we will briefly cover the basics of power analysis, linear mixed models, and why the combination of both requires a simulation-based approach. We will then focus on the R-package mixedpower and how to use it to estimate power in LMMs. The general aim of this workshop will be to help researchers build intuitions about simulation-based power analyses, and to empower them to set up highly powered research designs when they plan to use mixed-effect models to analyse the resultant data. A prerequisite for this workshop is a basic knowledge of R. Although we will briefly cover the basics of LMMs, familiarity with LMMs and the R-package lme4 is strongly recommended.
Speaker: Levi Kumle
Date: 17.05.2023, 10-12 a.m.
Number of Participants: Max. 25
Access requirements: Prior knowledge: at least basic working knowledge of R and RStudio since we will use that for the interactive components. I will probably give a 5 min introduction to mixed models, but some prior knowledge of mixed models (and preferably the lme4-package) would be helpful!
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