Predicting reliability through structured expert elicitation with the repliCATS (Collaborative Assessments for Trustworthy Science) process

Hannah Fraser (Lead / Corresponding author), Martin Bush (Lead / Corresponding author), Bonnie C. Wintle, Fallon Mody, Eden T. Smith, Anca M. Hanea, Elliot Gould, Victoria Hemming, Daniel G. Hamilton, Libby Rumpff, David P. Wilkinson, Ross Pearson, Felix Singleton Thorn, Raquel Ashton, Aaron Willcox, Charles T. Gray, Andrew Head, Melissa Ross, Rebecca Groenewegen, Alexandru MarcociAns Vercammen, Timothy H. Parker, Rink Hoekstra, Shinichi Nakagawa, David R. Mandel, Don van Ravenzwaaij, Marissa McBride, Richard O. Sinnott, Peter Vesk, Mark Burgman, Fiona Fidler

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Abstract

As replications of individual studies are resource intensive, techniques for predicting the replicability are required. We introduce the repliCATS (Collaborative Assessments for Trustworthy Science) process, a new method for eliciting expert predictions about the replicability of research. This process is a structured expert elicitation approach based on a modified Delphi technique applied to the evaluation of research claims in social and behavioural sciences. The utility of processes to predict replicability is their capacity to test scientific claims without the costs of full replication. Experimental data supports the validity of this process, with a validation study producing a classification accuracy of 84% and an Area Under the Curve of 0.94, meeting or exceeding the accuracy of other techniques used to predict replicability. The repliCATS process provides other benefits. It is highly scalable, able to be deployed for both rapid assessment of small numbers of claims, and assessment of high volumes of claims over an extended period through an online elicitation platform, having been used to assess 3000 research claims over an 18 month period. It is available to be implemented in a range of ways and we describe one such implementation. An important advantage of the repliCATS process is that it collects qualitative data that has the potential to provide insight in understanding the limits of generalizability of scientific claims. The primary limitation of the repliCATS process is its reliance on human-derived predictions with consequent costs in terms of participant fatigue although careful design can minimise these costs. The repliCATS process has potential applications in alternative peer review and in the allocation of effort for replication studies.

Original languageEnglish
Article numbere0274429
Number of pages16
JournalPLoS ONE
Volume18
DOIs
Publication statusPublished - 26 Jan 2023

Keywords

  • Humans
  • Reproducibility of Results
  • Costs and Cost Analysis
  • Data Accuracy
  • Behavioral Sciences
  • Peer Review

ASJC Scopus subject areas

  • General

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