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