What does it mean to replicate a research study and why is this important?
This activity consists of a series of videos that examine the different types of replication and the inherent differences between replications in the social sciences and those in the life sciences or physical sciences. It also introduces a viewpoint article by Dr. Daniel Hamermesh that discusses the importance of replication and how the scientific community can incentivize their publications. The next two videos focus on different aspects of Dr. Hamermesh’s paper. We also go into more depth below. Show Replicability and replication are very important to the process of ensuring the validity of scientific findings. Pure replications can verify that a past analysis was done correctly and statistical replications provide some sense that a study’s (or aggregated studies’) findings are valid. In the viewpoint article “Replication in Economics,” economist Daniel Hamermesh discusses both types of replication and examines why replication is so rare in published social science literature. Pure replications, which use the same data as previously published studies to check for errors, are disturbingly rare, at least in economics. Dr. Hamermesh sent a survey to authors of empirical studies published in two leading labor economics journals between 2002 and 2004: Industrial and Labor Relations Review (ILRR) and the Journal of Human Resources(JHR). He found that the vast majority of these authors never received requests of any kind for their data sets. Hamermesh then gives three positive incentives for research replicability and the sharing of data:
Hamermesh also gives advice to both researchers seeking to perform replications and authors whose studies have been replicated. In general, authors should make their data and code readily available and usable; replicating authors should “take a gentle, restrained professional tone in the comment”; and replicated authors should admit mistakes honestly and swiftly. He states that
He also suggests that journal editors take the lead on this issue by authoring a few highly visible and high quality replications of their own in order to provide a model for future replications, as well as to normalize the practice. Similarly rare are scientific replications (or statistical replications) that re-examine “an idea in some published research by studying it using a different data set chosen from a different population from that used in the original paper.” Such replications are extremely important to the external validity of studies. Hamermesh asserts:
Furthermore, “[i]f our theories are intended to be general, to describe the behaviour of consumers, firms, or markets independent of the social or broader economic context, they should be tested using data from more than just one economy.” Within-study replications, or studies that use multiple datasets, either from temporally or geographically distant sources, are currently our best bet for scientific replication in the social sciences since there are few incentives for journal editors to publish externally replicated research as “the profession puts a premium on the creativity and generality of the idea, not on verifying the breadth of its applicability.” Hamermesh concedes, however, that “the incentives for doing within-study scientific replication are non-existent.” Thus, he declares that “it is crucial that editors of the leading journals tilt the publishing process a bit more in favour of within-study scientific replication.” What are the incentives for a researcher to replicate another’s data, code, or study? You can read the full paper here. Reference Hamermesh, Daniel S. 2007. “Viewpoint: Replication in Economics.” Canadian Journal of Economics/Revue Canadienne D’économique 40 (3): 715–33. doi:10.1111/j.1365-2966.2007.00428.x. Why is it important to replicate a research study?Replication is one of the key ways scientists build confidence in the scientific merit of results. When the result from one study is found to be consistent by another study, it is more likely to represent a reliable claim to new knowledge.
Why are replicate samples important?Replicates can be used to measure variation in the experiment so that statistical tests can be applied to evaluate differences. Averaging across replicates increases the precision of gene expression measurements and allows smaller changes to be detected.
What does it mean to replicate a study?To replicate an experiment, researchers use the same methods of data collection and apply the same analysis, even though they have to use new subjects, often in somewhat different situations. Subjects may be generally older or younger, for example, or from a different country.
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