Teaching reproducibility for stats beginners – give me seven ideas!

I’m teaching reproducibility as part of a lecture for statistics beginners in the social sciences. I reserved seven slides for that and I have 15 minutes. What would you include?

I’m thinking of these topics, and I would really need input on how to rank these, or additions on what I missed. Please comment below or on twitter (@polscireplicate).

• Definition of reproducibility and research transparency
• Recent scandals in the social sciences
• How to save your project files in a transparent way (structuring your files)
• Software tools 1: Rstudio and Rscripts
• Software tool 2: knitr and R markdown
• What can happen if you don’t work reproducibly
• …

If you know of lecture slides or other materials, please share the links so I can give them to my students. I will also publish a link list on this blog. Thank you!

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Reblog: Replication in political science graduate courses: an untapped resource?

A post I published with Seth Werfel and Stephanie Wykstra on The Monkey Cage blog discusses survey results about replication projects assigned in graduate courses.

Setting up a replication workshop: Why it’s worth it & what to do better

More and more scholars integrate replication into their teaching, for example Gary King, Victoria Stodden, Chris Fariss, Jamie Monogan. With the second edition of the Replication Workshop starting today, here’s why it’s worth it, and how to improve teaching that includes replication – based on what my TAs said after the last Cambridge Replication Workshop.

Replication chains: Political tolerance taken apart

How would you like it if someone replicated your paper? Will it help you, and give you more citations, or will it cause rage? Some authors defend their original work against replication by writing an ‘answer’ paper, and they might claim that the replication was fundamentally flawed or contained statistical and reporting errors. Here’s another interesting replication chain.

Replication chains: voter calls and turnout

Sometimes an author, when being replicated by someone, answers to that replication in a new paper. In that new paper (s)he again might replicate some of the disputed results. Most authors defend their earlier paper by claiming that the replication was: fundamentally flawed, contains statistical and reporting errors, is of trivial nature, or less realistic and of limited utility. Such replication chains are not just entertaining academic slugfest, but they are useful because they provide detailed discussions about data and methods in the field.

Setting up a replication workshop – suggestions needed

I’m starting a replication workshop with my statistics students. During my lectures in basic statistics I found that students were most engaged in lab sessions when we worked with data sets. I want to build on that and use replication as a new teaching tool, and I will report about this on my blog. My first challenge: How to pick a paper that’s simple enough for statistics beginners?