ShinyItemAnalysis: Test and Item Analysis via Shiny

#' AIBS grant peer review scoring dataset
#'
#' @description The \code{AIBS} dataset (Gallo, 2020) comes from the scientific
#'   peer review facilitated by the American Institute of Biological Sciences (AIBS)
#'   of biomedical applications from and intramural collaborative biomedical research
#'   program for 2014--2017. For each proposal, three assigned individual reviewers were
#'   asked to provide scores and commentary for the following application criteria:
#'   Innovation, Approach/Feasibility, Investigator, and Significance (Impact added
#'   as scored criterion in 2014). Each of these criteria is scored on a scale from
#'   1.0 (best) to 5.0 (worst) with a 0.1 gradation, as well as an overall score
#'   (1.0--5.0 with a 0.1 gradation). Asynchronous discussion was allowed, although
#'   few scores changed post-discussion. The data includes reviewers' self-reported
#'   expertise scores (1/2/3, 1 is high expertise) relative to each proposal reviewed,
#'   and reviewer / principal investigator demographics. A total of 72
#'   applications ("Standard" or "Pilot") were reviewed in 3 review cycles. The
#'   success rate was 34--38\%. Application scores indicate where each application
#'   falls among all practically possible applications in comparison with the
#'   ideal standard of quality from a perfect application. The dataset was used by
#'   Erosheva et al. (2021a) to demonstrate issues of inter-rater reliability in
#'   case of restricted samples. For details, see Erosheva et al. (2021b).
#'
#' @usage data(AIBS)
#'
#' @author Stephen Gallo \cr American Institute of Biological Sciences
#'
#' @references
#' Gallo, S. (2021). Grant  peer  review  scoring  data  with  criteria  scores.
#' \doi{10.6084/m9.figshare.12728087}
#'
#' Erosheva, E., Martinkova, P., & Lee, C. (2021a). When zero may not be zero: A
#' cautionary note on the use of inter-rater reliability in evaluating grant
#' peer review. Journal of the Royal Statistical Society - Series A.
#' \doi{10.1111/rssa.12681}
#'
#' Erosheva, E., Martinkova, P., & Lee, C. (2021b). Supplementary material: When
#' zero may not be zero: A cautionary note on the use of inter-rater reliability
#' in evaluating grant peer review. \doi{10.17605/OSF.IO/KNPH8}
#'
#' @keywords datasets
#'
#' @seealso
#' \code{\link{ICCrestricted}}
#'
#' @format \code{AIBS} is a \code{data.frame} consisting of 216 observations on
#'   25 variables. Data describes 72 proposals with 3 ratings each.
#'   \describe{
#'   \item{ID}{Proposal ID. }
#'   \item{Year}{Year of the review. }
#'   \item{PropType}{Proposal type; \code{"Standard"} or \code{"Pilot"}. }
#'   \item{PIID}{Anonymized ID of principal investigator (PI). }
#'   \item{PIOrgType}{PI's organization type. }
#'   \item{PIGender}{PI's gender membership; \code{"1"} females, \code{"2"} males. }
#'   \item{PIRank}{PI's rank; \code{"3"} full professor, \code{"1"} assistant professor. }
#'   \item{PIDegree}{PI's degree; \code{"1"} PhD, \code{"2"} MD, \code{"3"} PhD/MD. }
#'   \item{Innovation}{Innovation score. }
#'   \item{Approach}{Approach score. }
#'   \item{Investig}{Investigator score. }
#'   \item{Signif}{Significance score. }
#'   \item{Impact}{Impact score. }
#'   \item{Score}{Scientific merit (overall) score. }
#'   \item{ScoreAvg}{Average of the three overall scores from three different reviewers. }
#'   \item{ScoreAvgAdj}{Average of the three overall scores from three different reviewers, increased by multiple of 0.001 of the worst score. }
#'   \item{ScoreRank}{Project rank calculated based on \code{ScoreAvg}. }
#'   \item{ScoreRankAdj}{Project rank calculated based on \code{ScoreAvgAdj}. }
#'   \item{RevID}{Reviewer's ID. }
#'   \item{RevExp}{Reviewer's experience. }
#'   \item{RevInst}{Reviewer's institution; \code{"1"} academia, \code{"2"} government. }
#'   \item{RevGender}{Reviewer's gender; \code{"1"} females, \code{"2"} males. }
#'   \item{RevRank}{Reviewer's rank; \code{"3"} full professor, \code{"1"} assistant professor. }
#'   \item{RevDegree}{Reviewer's degree; \code{"1"} PhD, \code{"2"} MD, \code{"3"} PhD/MD. }
#'   \item{RevCode}{Reviewer code (\code{"A"}, \code{"B"}, \code{"C"}) in the original wide dataset. }
#' }
"AIBS"