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:
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Experiment design, and planning sample size using simulated data
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Defining the analysis plan using simulated data
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Checking that your experiment software actually collects the data you need
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Once data are collected, visualizing and summarizing the data
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Creating an R package to document and release your data and analyses
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Code refactoring
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Integrating the data analysis into the manuscript
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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