doi:10.1371/journal.pone.0256919>. The package also provides functions to visualise and evaluate the performance of your aggregated estimates on validation data.">

aggreCAT: Mathematically Aggregating Expert Judgments (original) (raw)

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.

Version: 1.0.0
Depends: R (≥ 2.10)
Imports: magrittr, GoFKernel, purrr, R2jags, coda, precrec, mathjaxr, cli, VGAM, crayon, dplyr, stringr, tidyr, tibble, ggplot2, insight, DescTools, MLmetrics
Suggests: testthat (≥ 2.1.0), knitr, rmarkdown, covr, pointblank, janitor, qualtRics, here, readxl, readr, stats, lubridate, forcats, ggforce, ggpubr, ggridges, rjags, tidybayes, tidyverse, usethis, nlme, gt, gtExtras, R.rsp
Published: 2025-05-28
DOI: 10.32614/CRAN.package.aggreCAT
Author: David Wilkinson ORCID iD [aut, cre], Elliot Gould ORCID iD [aut], Aaron Willcox ORCID iD [aut], Charles T. Gray [aut], Rose E. O'Dea ORCID iD [aut], Rebecca GroenewegenORCID iD [aut]
Maintainer: David Wilkinson <david.wilkinson.research at gmail.com>
License: MIT + file
URL: https://replicats.research.unimelb.edu.au/
NeedsCompilation: no
Citation: aggreCAT citation info
Materials: README, NEWS
CRAN checks: aggreCAT results

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