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 + fileLICENSE |
| URL: | https://replicats.research.unimelb.edu.au/ |
| NeedsCompilation: | no |
| Citation: | aggreCAT citation info |
| Materials: | README,NEWS |
| CRAN checks: | aggreCAT results |