R/screenr-package.R

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

#' screenr Package
#'
#' @description
#' The \code{screenr} package enables construction of binary test-screening
#' tools.  It is designed to enable those with only a basic familiarity with
#' \code{R} to develop, validate and implement screening tools for diagnostic
#' tests.  \code{screenr} integrates the capabilities of the \code{glm},
#' \code{glmpath} and \code{pROC} packages for convenience and ease of use.
#'
#' Consider the situation where a diagnostic test for some condition is
#' relatively expensive, and the condition is rare.  In that case, universal
#' testing would not be efficient in terms of the yield of postive results per
#' test performed.  Now suppose that responses to a set of simple screening
#' questions may be predictive of the condition.  Package \code{screenr} enables
#' estimation of thresholds for making decisions about when to test in order to
#' screen in/out individuals based on Receiver Operating Characteristics (ROC)
#' estimated from an initial sample.  The choice of a particular screening
#' threshold is left to the user, and should be based on careful consideration
#' of application-specific tradeoffs between sensitivity and specificity.
#' \code{screenr} also enables easy construction of screening tools.
#'
#' A tutorial is available from \code{vignette("screenr_Tutorial", package = "screenr")}.
#'
#' The pdf versions of the package manual and the tutorial are available at
#' \url{https://github.com/sgutreuter/screenr}.
#'
#' @details
#' The high-level functions in the \code{screenr} package are:
#' \describe{
#' \item{\code{\link{lasso_screenr}}}{Selection of logistic models based on GLM
#' path regularization}
#' \item{\code{\link{logreg_screenr}}}{Test-screening based maximum-likelhood
#' estimation of logistic models}
#' \item{\code{\link{gee_screenr}}}{Test-screening based GEE estimation
#' of logistic models accounting for cluster sampling}
#' \item{\code{\link{easy_tool}}}{Easy implementation of test-screening tools}
#' \item{\code{\link{simple_screenr}}}{(Too) simple un-optimized test-screening}
#' \item{\code{\link{rescale_to_int}}}{Rescale a strictly positive vector of
#' real numbers to integers}
#' \item{\code{\link{sens_spec_plus}}}{Sensitivity, specificity and friends}
#' }
#'
#' \code{screenr} provides the usual \code{plot}, \code{print}, \code{summary},
#' \code{predict} methods for the objects produced by \code{lasso_screenr},
#' \code{logreg_screenr}, \code{gee_screenr}, \code{simple_screenr} and
#' \code{easy_tool}, and also
#' \code{coef} and \code{confint} methods for \code{lasso_screenr},
#' \code{gee_screenr} and \code{logreg_screenr} objects.
#' \code{screenr} also provides \code{get_what} methods to extract object
#' components, and \code{ntpp} methods for computation of the average number of
#' tests required to detect a single positive result and the residual
#' positivity among those screened out of testing.
#'
#' @references
#'
#' Teferi W, Gutreuter S, Bekele A et al. Adapting strategies for effective and
#' efficient pediatric HIV case finding: Risk screening tool for testing children
#' presenting at high-risk entry points. BMC Infectious Diseases. 2022; 22:480.
#' \url{http://doi.org/10.1186/s12879-022-07460-w}
#'
#' @note
#' The canonical source repository for \code{screenr} is
#' \url{https://github.com/sgutreuter/screenr}
#'
#' @name screenr
#' @docType package
#' @author Steve Gutreuter: \email{sgutreuter@gmail.com}
NULL