Concurrent Replication

I’m working on a paper with Alex Etz, Rich Lucas, and Brent Donnellan. We had to cut 2,000 words and the text below is one of the darlings we killed. I’m reviving it as a blog post here because even though it made sense to cut the segment from the manuscript (I cut it myself, the others didn’t make me), the notion of concurrent replication is an important one.

The current replication debate has, for various reasons, construed replication as a retrospective process. A research group decides to replicate a finding that is already in the published literature. Some of the most high-profile replication studies, for example, have focused on findings published decades earlier, for example the registered replication projects on verbal overshadowing (Alogna et al, 2014) and facial feedback (Wagenmakers et al., in press). This retrospective approach, however timely and important, might be partially responsible for the controversial reputation that replication currently enjoys.

A form of replication that has received not much attention yet is what I will call concurrent replication. The basic idea is this. A research group formulates a hypothesis that they want to test. At the same time, they desire to have some reassurance about the reliability of the finding they expect to obtain. They decide to team up with another research group. They provide this group with a protocol for the experiment, the program and stimuli to run the experiment, and the code for the statistical analysis of the data. The experiment is preregistered. Both groups then each run the experiment and analyze the data independently. The results of both studies are included in the article, along with a meta-analysis of the results. This is the simplest variant. A concurrent replication effort can involve more groups of researchers.

A direct exchange of experiments (a straight “study swap”) is the simplest model of concurrent replication. It is possible to accomplish such study swaps on a larger scale where participating labs offer and request subject hours. This will likely result in a network of labs each potentially simultaneously engaged in forming and testing novel hypotheses as well as concurrently replicating hypotheses formed by other labs. The Open Science Framework features a site that has recently been developed to facilitate concurrent replication, Study Swap, see also this article.  At the time of this writing, there are four projects listed on Study Swap. We hope this number will increase soon.

Aside from this, there already are several large-scale concurrent replication efforts. An example is the Pipeline Project, a systematic effort to conduct prepublication replications, independently performed by separate labs. The first instalment was recently published (Schweisberg et al. 2016) and a second project is underway.

Concurrent replication has several advantages. First, researchers have a better sense of the reliability of their findings prior to publication.  After all, the results have been independently replicated before submission of the article. Likewise, journal editors and reviewers will have more confidence in the findings reported in the manuscript they are asked to evaluate. Journals have the luxury of publishing findings that have already been independently replicated. As a result, the reproducibility of the findings in the literature will start to increase. The Schweisberg et al. (2016) study demonstrates that concurrent replication is not only possible but also useful.

Concurrent replication forces researchers to be explicit about the procedure by which they expect to obtain the effect. If they do indeed obtain the finding both in the original study and in an independent replication, they have what amounts to a scientific finding according to the criteria established by Popper: They can describe a procedure by which the finding can reliably be produced. It will be easy and natural to include the protocol into the method section of the article. A positive side-effect of this will be a marked improvement in the quality of method sections in the literature. As a result, researchers who want to build on these findings have two advantages that researchers currently do not enjoy. First, they can build on a firmer foundation. After all, the reported finding has already been independently replicated. Second, a replication recipe doesn’t have to be laboriously reconstructed. It is readily available in the article.

Of course, concurrent replication is not without challenges. For instance, how should authorship be determined given such an arrangement? A flexible approach is best here. At one extreme the original group’s hypothesis might be very close to the replicating group’s own interest. In this case it would therefore be logical to make members of both groups co-authors; each group may have something to add to the paper both in terms of data and analysis and in terms of theory. At the other extreme, the second group has no direct interest in the hypothesis but may be willing to run a replication, perhaps in exchange for a replication of one of their own experiments. In this case it might be sufficient to acknowledge the other group’s involvement without offering co-authorship.

Thus far, the discussion here has only involved a scenario in which the hypothesis is supported in both the initiating as in the replicating lab. However, other scenarios are also possible. The second scenario is one in which the hypothesis is supported in one of the labs but not in the other. If the meta-analysis shows heterogeneity among the findings, researchers might hypothesize about a potential difference between the experiments, preregister that hypothesis and test it, again with a direct replication. If the meta-analysis does not show heterogeneity, it might be decided that it is sufficient to report the meta-analytic effect. If neither lab shows the effect, the research groups might report the results without engaging in follow-up studies. Alternatively, they might decide the experimental procedure was suboptimal, revise it, preregister the new experiment and run it, along with one or more concurrent replications.

To summarize, concurrent replication forms an underrepresented but potentially extremely valuable form of replication. Several concurrent large-scale replication efforts are currently underway and a platform that also facilitates conducting smaller-scale projects is available for use. The fact that concurrent replications are often viewed positively by the field is further evidence of the importance of replication for scientific endeavors.

References

Alogna, V. K., Attaya, M. K., Aucoin, P., Bahnik, S., Birch, S., Birt, A. R., ... Zwaan, R. A. (2014). Registered replication report: Schooler & Engstler-Schooler (1990). Perspectives on Psychological Science, 9, 556–578.

Schweinsberg, M. et al. (2016). The pipeline project: pre-publication independent replications of a single laboratory's research pipeline. journal of experimental social psychology, 66, 55–67.

Wagenmakers, E.-J., Beek, T., Dijkhoff, L., Gronau, Q. F., Acosta, A., Adams, R. B., Jr., . . . Zwaan, R. A. (2016). Registered Replication Report: Strack, Martin, & Stepper (1988). Perspectives on Psychological Science, 11, 917–928.