#' @title Fictional pandemic data
#'
#' @description
#'
#' An entirely artificially constructed data set and context designed for classroom discussion and
#' analysis.
#'
#' The data (and the fictional narrative below) are identical to those of \code{\link{trtPan}};
#' the only difference is the organization of the data.
#' Which organization the instructor might choose depends upon the modelling
#' and/or data manipulation is intended for analysis.
#'
#' Should raise interesting scientific questions on how the results should, or should not, be
#' interpreted. It should also raise questions on what might be done next.
#'
#' A "pandemic" context is given in the details since the data were created during the first week of
#' March, 2020.
#'
#' Instructors might choose to invent their own context.
#'
#'
#' @format A data frame with 100 rows and 4 variables
#' \describe{
#' \item{City}{City for which the outcome data were recorded. }
#' \item{A}{The percent survival rate for infected persons given medical treatment "A".}
#' \item{B}{The percent survival rate for infected persons given medical treatment "B".}
#' \item{C}{The percent survival rate for infected persons given medical treatment "C".}
#' }
#'
#'
#' @details
#'
#' One fictional narrative for this data set is as follows.
#'
#' A virulent virus has led to a world wide pandemic and that the case fatality rate
#' (proportion of those infected who die) is huge (say 6%) in some age group.
#'
#' Suppose that through a concerted and collaborative effort of health scientists worldwide,
#' three different treatments have been developed for this group.
#' All three treatments have been used at one time or another on numerous patients in
#' this group from 100 different cities worldwide.
#' The data are observational, in that they were simply collected and the treatment given noted.
#' No information is available on why one treatment or another was given in any particular instance.
#'
#' The recovery rates (as a percent) for the patients treated by each of the three treatments
#' were simply recorded for each of the hundred cities and are available for analysis as the
#' data frame \code{pandemic}.
#'
#' Some obvious questions of interest are the comparisons of treatments. For example, is treatment
#' A better than B? Than C? Is B better than C?
#'
#' @docType data
#'
#' @name pandemic
#'
#' @seealso
#' \code{\link{trtPan}}
#' \code{\link{medicalRecords}} \code{\link{covidNZ}}
#'
#' @keywords fictional medicine paradox teaching
#'
#' @author
#' R.W. Oldford
#'
NULL
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