I’m an assistant professor in the Department of Social Psychology at Tilburg University. On this website you can find information about what I study, the projects I’m involved in, and blog posts about various topics related to my work. Some notable projects I’m working on are tidystats and a large-scaled replication study of cognitive dissonance.Learn more
Introduction In a previous post I covered how to perform simulation-based power analyses. A limitation in that post is that usually the question is not what our power is, but rather which sample size gives us the desired power. With the code from my previous post you can get to the right sample size by changing the sample size parameters and then checking whether this gives you enough power.
Introduction Setup One Sample t-test Welch’s Two Sample t-test Two Sample t-test Paired t-test Correlation 2 t-tests Regression (2 x 2 interaction) Conclusion Introduction Doing power analyses is hard. I know this from experience, both as a researcher and as a reviewer. As a researcher, I have found power analyses to be difficult because performing a good power analysis requires a thorough understanding of the (hypothesized) data.
Method sections in academic (psychology) papers usually consist of the following sections: Participants, Design, Procedure, and Materials. They also tend to be presented in this order. But is this, generally speaking, the right order? I don’t think so. I think the proper order of Method sections is: Design Procedure Materials Data Analysis Participants Two things are notable here. One, there’s a Data Analysis section. Two, the Participants section is all the way at the end.
I’m an assistant professor in the Social Psychology department of Tilburg University. I have about 10 years of research experience, with publications of both scientific papers in peer-reviewed journals, as well as software publications. It should be no surprise then that my skill set consists of research skills (e.g., experimental design, data analysis, writing) and technical skills (e.g., programming).Learn more