Package: aggreCAT
Title: Mathematically Aggregating Expert Judgments
Version: 1.0.0
Authors@R: c(person(given = "David", 
                    family = "Wilkinson", 
                    role = c("aut", "cre"),
                    email = "david.wilkinson.research@gmail.com",
                    comment = structure("0000-0002-9560-6499", .Names = "ORCID")),
             person(given = "Elliot", 
                    family = "Gould", 
                    role = "aut", 
                    comment = structure("0000-0002-6585-538X", .Names = "ORCID")),
             person(given = "Aaron", 
                    family = "Willcox", 
                    role = "aut",
                    email = " aaron@willcox.io",
                    comment = structure("0000-0003-2536-2596", .Names = "ORCID")),
             person(given = "Charles T.",
                    family = "Gray",
                    role = c("aut")),
             person(given = "Rose", 
                    family = "E. O'Dea", 
                    role = "aut", 
                    comment = structure("0000-0001-8177-5075", .Names = "ORCID")),
             person(given = "Rebecca",
                    family = "Groenewegen",
                    role = "aut",
                    comment = structure("0000-0001-9177-8536", .Names = "ORCID")))
Description: 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.
URL: https://replicats.research.unimelb.edu.au/
License: MIT + file LICENSE
Encoding: UTF-8
LazyData: true
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
RoxygenNote: 7.2.3
Depends: R (>= 2.10)
Imports: magrittr, GoFKernel, purrr, R2jags, coda, precrec, mathjaxr,
        cli, VGAM, crayon, dplyr, stringr, tidyr, tibble, ggplot2,
        insight, DescTools, MLmetrics
VignetteBuilder: knitr, R.rsp
RdMacros: mathjaxr
Config/testthat/parallel: true
Config/testthat/edition: 3
NeedsCompilation: no
Packaged: 2025-05-26 13:28:03 UTC; wilko
Author: David 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>)
Maintainer: David Wilkinson <david.wilkinson.research@gmail.com>
Repository: CRAN
Date/Publication: 2025-05-28 15:30:02 UTC
Built: R 4.6.0; ; 2025-10-14 03:50:47 UTC; windows
