aggreCAT: Mathematically Aggregating Expert Judgments

The use of structured elicitation to inform decision making has grown dramatically in recent decades, however, judgements from multiple experts must be aggregated into a single estimate. Empirical evidence suggests that mathematical aggregation provides more reliable estimates than enforcing behavioural consensus on group estimates. 'aggreCAT' provides state-of-the-art mathematical aggregation methods for elicitation data including those defined in Hanea, A. et al. (2021) <doi:10.1371/journal.pone.0256919>. The package also provides functions to visualise and evaluate the performance of your aggregated estimates on validation data.

Getting started

Package details

AuthorDavid Wilkinson [aut, cre] (ORCID: <https://orcid.org/0000-0002-9560-6499>), Elliot Gould [aut] (ORCID: <https://orcid.org/0000-0002-6585-538X>), Aaron Willcox [aut] (ORCID: <https://orcid.org/0000-0003-2536-2596>), Charles T. Gray [aut], Rose E. O'Dea [aut] (ORCID: <https://orcid.org/0000-0001-8177-5075>), Rebecca Groenewegen [aut] (ORCID: <https://orcid.org/0000-0001-9177-8536>)
MaintainerDavid Wilkinson <david.wilkinson.research@gmail.com>
LicenseMIT + file LICENSE
Version1.0.0
URL https://replicats.research.unimelb.edu.au/
Package repositoryView on CRAN
Installation Install the latest version of this package by entering the following in R:
install.packages("aggreCAT")

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aggreCAT documentation built on June 8, 2025, 11:06 a.m.