Power analyses

Within this session we’ll spend a fair amount of time on talking about power analyses, effect sizes, design efficiency and sample size calculations as a necessary prerequisite regarding study planning, interpretation and outcome sharing, again also with a focus on open & reproducible science as well as FAIR principles.

Setting up and planning a new study is hard and super complex. Among the most crucial factors are setting up a design that in combination with a certain sample size can achieve enough power to detect an effect of interest. However, it’s worse without clear outlines, documentation and standardization. More and more, a respective a-prior power analysis or sample size calculation is required by IRB, for grants, for pre-prints, etc. . However, what are the important steps of the respective approaches & how should they be conducted? At what point do I need think about incorporating open & reproducible science? Are there tools & resources I can use? All these and more questions will be addressed in this session.

Objectives📍

• learn about aspects of power analyses, design efficiency & effect sizes

• get to know respective tools & resources

• Ask and answer questions

• Have a great time

Slides 📓

Below you’ll find the slides we went through during the session. However, we recommend scrolling further for the more narrative version of the content.

You can directly access the slides here.

optional tasks based on this session 🖥️✍🏽📖

Below you’ll find the tasks you should spend a look at if you want to further work on and evaluate the aspects we talked about in this session.