R/ad_data.R

In modeldata: Data Sets Useful for Modeling Examples

#' Alzheimer's disease data
#'
#' @details
#' Craig-Schapiro et al. (2011) describe a clinical study of 333 patients,
#'  including some with mild (but well-characterized) cognitive impairment as
#'  well as healthy individuals. CSF samples were taken from all subjects. The
#'  goal of the study was to determine if subjects in the early states of
#'  impairment could be differentiated from cognitively healthy individuals.
#'  Data collected on each subject included:
#' \itemize{
#' \item Demographic characteristics such as age and gender
#' \item Apolipoprotein E genotype
#' \item Protein measurements of Abeta, Tau, and a phosphorylated version of Tau (called pTau)
#' \item Proteinmeasurements of 124 exploratory biomarkers, and
#' \item Clinical dementia scores
#' }
#'
#' For these analyses, we have converted the scores to two classes: impaired
#'  and healthy. The goal of this analysis is to create classification models
#'  using the demographic and assay data to predict which patients have early
#'  stages of disease.
#'
#' @name ad_data
#' @aliases ad_data
#' @docType data
#' @return \item{ad_data}{a tibble}
#'
#' @source
#' Kuhn, M., Johnson, K. (2013) *Applied Predictive Modeling*, Springer.
#'
#' Craig-Schapiro R, Kuhn M, Xiong C, Pickering EH, Liu J, Misko TP, et al.
#' (2011) Multiplexed Immunoassay Panel Identifies Novel CSF Biomarkers for
#' Alzheimer's Disease Diagnosis and Prognosis. PLoS ONE 6(4): e18850.
#'
#'
#' @keywords datasets
#' @examples
#' data(ad_data)
#' str(ad_data)
NULL