Tutorials
Some of the below projects are tutorials in the sense that they include step-by-step instructions, whereas others just represent coding projects with comments.
The topics covered are all connected to open science, meta-science and reproducibility and available via my GitHub account.
They are free to download and use in the hope that they can be somewhat useful to others.
A reproducible scientific workflow in R and R Studio
This project tries to outline a reproducible scientific workflow using R and R Studio that starts with raw data and ends with the finished manuscript.
A Bayesian workflow
This project takes aspects of the Bayesian workflow paper by Gelman and colleagues and applies them to an example scenario in experimental psychology.
A PsychoPy Tutorial
This tutorial is intended as a one-stop guide to understanding and using PsychoPy/Pavlovia. Andrew Wildman was the primary author.
Data simulation to determine sample sizes
This project simulates multi-level data for a range of factorial designs.
https://github.com/rich-ramsey/sim_demo
And this one does the same for “small-N” designs, where trial counts per participant are particularly important.
Analysing pupilomoetry data using hgams
This project tries to provide an example of how you might model pupilometry data using hierarchical generalised additive models (hgams).