# power

## Example power analysis report

Context In one of my recent Twitter posts, I got pissy and complained about a vague power-analysis statement I saw while reviewing a manuscript submitted to a scientific journal.

## Bayesian power analysis: Part III.b. What about 0/1 data?

Version 1.1.0 Edited on April 21, 2021, to fix a few code breaks and add a Reference section. Orientation In the last post, we covered how the Poisson distribution is handy for modeling count data.

## Bayesian power analysis: Part III.a. Counts are special.

Version 1.1.0 Edited on April 21, 2021, to remove the broom::tidy() portion of the workflow. Orientation So far we’ve covered Bayesian power simulations from both a null hypothesis orientation (see part I) and a parameter width perspective (see part II).

## Bayesian power analysis: Part II. Some might prefer precision to power

Version 1.1.0 Edited on April 21, 2021, to remove the broom::tidy() portion of the workflow. tl;dr When researchers decide on a sample size for an upcoming project, there are more things to consider than null-hypothesis-oriented power.

## Bayesian power analysis: Part I. Prepare to reject $H_0$ with simulation.

Version 1.1.0 Edited on April 21, 2021, to remove the broom::tidy() portion of the workflow. tl;dr If you’d like to learn how to do Bayesian power calculations using brms, stick around for this multi-part blog series.