R/unicorns-data.R

In sgutreuter/screenr: Construction of Binary Test-Screening Rules

#' UIV Testing Training Data on Unicorns
#'
#' A preliminary study was conducted in which a random sample of 6,000 properly
#' consented [unicorns](https://www.britannica.com/topic/unicorn) were recruited
#' from 20 clinics.  Each unicorn was asked
#' seven questions about their behavior and health.  Unicorns responded by
#' stomping a hoof once to indicate "no", and twice to indicate "yes".  A
#' sample of venous blood was drawn from each, and was subsequently tested
#' for the presence of antibodies to Unicorn Immunodeficiency Virus (UIV) using
#' a standard assay algorithm.
#'
#' @docType data
#'
#' @usage data(unicorns)
#'
#' @keywords datasets
#'
#' @format
#' A data frame with eight columns:
#' \describe{
#' \item{\code{ID}}{Patient ID}
#' \item{\code{Q1}}{Response to screening question 1 (0 = "no", 1 = "yes")}
#' \item{\code{Q2}}{Response to screening question 2 (0 = "no", 1 = "yes")}
#' \item{\code{Q3}}{Response to screening question 3 (0 = "no", 1 = "yes")}
#' \item{\code{Q4}}{Response to screening question 4 (0 = "no", 1 = "yes")}
#' \item{\code{Q5}}{Response to screening question 5 (0 = "no", 1 = "yes")}
#' \item{\code{Q6}}{Response to screening question 6 (0 = "no", 1 = "yes")}
#' \item{\code{Q7}}{Response to screening question 7 (0 = "no", 1 = "yes")}
#' \item{\code{testresult}}{UIV status, where 0 and 1 denote negative and positive test results, repectively.}
#' }
#'
#' @note
#' In reality, the question responses and test results were generated using
#' Bernoulli random-number generators.
#'
#' @examples
#' \dontrun{
#' head(unicorns)
#' }
"unicorns"