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 
[aut, cre],
Elliot Gould
[aut],
Aaron Willcox
[aut],
Charles T. Gray [aut],
Rose E. O'Dea
[aut],
Rebecca Groenewegen
[aut] |
| Maintainer: |
David Wilkinson <david.wilkinson.research at gmail.com> |
| License: |
MIT + file LICENSE |
| URL: |
https://replicats.research.unimelb.edu.au/ |
| NeedsCompilation: |
no |
| Citation: |
aggreCAT citation info |
| Materials: |
README, NEWS |
| CRAN checks: |
aggreCAT results |