aggreCAT: An R Package for Mathematically Aggregating Expert Judgments
Structured protocols, such as the IDEA protocol, may be used to elicit expert judgments in the form of subjective probabilities from multiple experts. Judgments from individual experts about a particular phenomena must therefore be mathematically aggregated into a single prediction. The process of aggregation may be complicated when uncertainty bounds are elicited with a judgment, and also when there are several rounds of elicitation. This paper presents the new R package \pkg{aggreCAT}, which provides 22 unique aggregation methods for combining individual judgments into a single, probabilistic measure. The aggregation methods were developed as a part of the Defense Advanced Research Projects Agency (DARPA) ‘Systematizing Confidence in Open Research and Evidence’ (SCORE) programme, which aims to generate confidence scores or estimates of ‘claim credibility’ for 3000 research claims from the social and behavioural sciences. We provide several worked examples illustrating the underlying mechanics of the aggregation methods. We also describe a general workflow for using the software in practice to facilitate uptake of this software for appropriate use-cases.