How to ask for data – nicely

I recently received an email where a graduate student is trying to ask original authors for data. There is some evidence that authors withhold data due to time constraints (Tenopir et al. 2011), but they may also decline to share data because they fear a damaged reputation when a replication of their work fails (Lupia and Elman 2014). From my experience in the Cambridge Replication Workshop, authors are more willing to share their data when the replicator is perceived as trying to be helpful rather than cross-checking results. Here are my tips.

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Coding errors can be avoided

An article in the American Journal of Political Science was corrected after the coding of a political attitude variable was accidentally the wrong way around. Pre-publication cross-checks by the authors and the journal, as well as publication of the original data and variable transformations can avoid such problems.

Vote for my blog to get Duckies award

For those who have found this blog useful, please consider putting in your vote for an award for Online Achievement in International Studies.

Getting the idea of transparency all wrong

Following an article in the New England Journal of Medicine, which portrayed scientists who re-use data as parasites, we now hear more on this from Nature. Apparently, data transparency is a menace to the public. The Nature comment “Don’t let transparency damage science” claims that the research community must protect authors from harassment by replicators. The piece further infects the discussion about openness with more absurd ideas that don’t reflect reality, and it leads the discussion backwards, not forward. 

Don’t review articles that withhold data

Journal editors can enforce replication policies. Authors can decide to work transparently. Most initiatives for open science and reproducibility agree that editors and authors are  are the key actors to enforce the gold standard of research integrity. However, peer-reviewers can use their leverage as well: just say you will only review an article once the author provides the data.

Reproducible Research in Biomedical Science – We’re not there yet

A new PLoS Biol aper on reproducible research practices across the biomedical literature examines if authors provide all data, code and funding information. The results are devastating.

“People like stories” A short film about reproducibility

We need mathematical help to tell the difference between a real discovery and the illusion of one. Fellow of the Royal Society and future President of the Royal Statistical Society, Sir David Spiegelhalter visits Dr Nicole Janz  to discuss reproducibility in scientific publications. Here’s the film:

Published articles understate the probability of type I errors

Can we trust published articles in political science? A recent paper suggests that we should be sceptic. When comparing the published results of survey experiments with the pre-registered plans for the same study, a lot of information gets lost. 80 percent of the studies failed to report all experimental conditions and planned outcomes.

How Reporting Statistical Significance Causes p-Value Hacking

A new article by researchers at the University of Amsterdam shows that publication bias towards statistically significant results may cause p-value misreporting. The team examined hundreds of published articles and found that authors had reported p-values < .05 when they were in fact larger. They conclude that publication bias may incentivize researchers to misreport results.

Re-Blog: Who’s afraid of open data? (by Dorothy Bishop on the BishopBlog)

“Well, how would you like it if you had spent years of your life gathering data … and some person you have never heard comes out of nowhere demanding to have it?” Dorothy Bishop wrote a very interesting blog post about a conference chat about someone who was forced to work transparently. Here’s the first few paragraphs – do check out the full text: