Event Open Science Initiative
- Date: Feb 12, 2020
- Time: 09:00 - 13:00
- Speaker: Shravan Vasishth
- Location: MPI for Human Cognitive and Brain Sciences
- Room: Charlotte Buehler Room (C402)
- Host: CBS Open Science
A recent analysis of publicly released data accompanying published papers in Cognition showed that not all published numbers could be reproduced, even though the data and code were available (https://royalsocietypublishing.org/doi/full/10.1098/rsos.180448). The authors state that: “…suboptimal data curation, unclear analysis specification and reporting errors can impede analytic reproducibility, undermining the utility of data sharing and the credibility of scientific findings.” In this workshop, I will suggest one way to minimize the chances of producing irreproducible results, focusing on repeated measures 2x2 factorial designs as a case study.
The steps I will discuss are:
Experiment design, and planning sample size using simulated data
Defining the analysis plan using simulated data
Checking that your experiment software actually collects the data you need
Once data are collected, visualizing and summarizing the data
Creating an R package to document and release your data and analyses
Code refactoring
Integrating the data analysis into the manuscript
Releasing data and code: a suggested checklist
You can download all materials from here.
If you use github, the archive can be cloned by typing the following on the command line:
git clone https://github.com/vasishth/ReproducibleWorkflows.git