Reacting to Replication Attempts

This is the first post in a three-part mini-series on replication research, to include posts on:

  • Why we should welcome replication attempts of our work
  • My own experience selecting and conducting replication studies
  • The case for offering up our own studies for replication, and how to do it via StudySwap

We should enthusiastically welcome replication attempts

How should we feel and how should we react when we learn that an independent research team either plans to conduct or has conducted a replication attempt of a finding we originally reported? I’ve prepared this flowchart to guide our reactions and elaborated a bit below.


Replication attempts are often perceived as and labeled as “tear down” missions. This response is counterproductive and we need to reframe the discussion surrounding replication attempts. To hear an excellent example of how we can do this, do yourself a favor and listen to this episode of the Black Goat. Sanjay Srivastava, Alexa Tullett, Simine Vazire, and Rich Lucas had a very interesting conversation about replication research and Rich shared some of his actual motivations for conducting replications (spoiler alert, it isn’t to crush souls and destroy careers).

As a starting point for my take on more productive responses to replication attempts of your work, let us assume that you are confident in the finding in question. If you are not, well, that’s another discussion for another time.

If you are confident in the finding, a replication attempt should be taken as a form flattery and a chance to enhance the visibility of your work. It suggests that someone in the field thinks the finding is important enough that we should have an accurate understanding of the finding or estimate of the size of an effect. If the replication attempt is ultimately published, then other members of the field agree on its importance.

The attempt “succeeds”

For example, the replication study finds an effect size very similar to your originally published effect size. Yay! An independent research team has supported the original finding and your confidence in the effect has grown with very little work on your part. You have been cited and received a big pat on the back from the data.

The attempt “fails”

For example, the replication study finds no effect or a much smaller effect size than you did originally. Of course, this will be initially frustrating. BUT, remember, you are confident in the finding. You have essentially been invited to a low-effort publication. Why? The journal will now almost certainly welcome a submission from you showing that you can, in fact, still get the finding. Heck, perhaps you and the replicating team can even work together to figure out what’s going on! This was exactly the positive and productive cycle that developed after we failed to replicate part of the Elaboration Likelihood Model’s predictions in Many Labs 3.

Original -> ML3 -> Response w/ data -> Response to the response w/ data

Charlie Ebersole has even provided some empirical evidence on how responses to “failed” replications are perceived. tl;dr: if one operates as a scientist should, by earnestly pursuing the truth and collaborating with replicators, such behavior will win you friends and enhance your scientific reputation.

So, buy your replicators a beer. You owe them one!

My next two posts will focus on my own experience selecting effects for replication attempts and how to offer up one’s own effects for independent replication.

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