R/dataDoc.R

In laderast/cvdRiskData: Synthetic Dataset for Cardiovascular Risk Prediction

#' CVD risk synthetic dataset
#'
#' A synthetic dataset for predicting cardiovascular risk in patient cohorts.
#' 
#'   \itemize{
#'     \item \code{patientID} Patient Identifier. Unique patient identifier for Health Hospital University.
#'     HHUID + 8 digit code
#'     \item \code{age} Patient Age Category. Age category of patient. string of age ranges.
#` Note that upper bound is not inclusive
#'     \item \code{htn} Does patient have hypertension? Threshold systolic blood pressure is 150. Y/N
#'     \item \code{treat} Is patient receiving hypertension treatment? Y/N
#'     \item \code{smoking} Y/N based on threshold of pack years: 10
#'     \item \code{race} Race based on self-defined question in survey. AmInd (american indian),
#'     Asian/PI (asian/pacific islander), Black/AfAm (Black/African American), White
#'     \item \code{gender} Gender of patient. Male, Female, NA means that patient did not want gender recorded.
#'     \item \code{t2d} Whether patient has Type 2 diabetes. Y/N.
#'     \item \code{numAge} numerical age in years.
#'     \item \code{bmi} Body Mass Index of Patient. kg/m^2
#'     \item \code{sbp} Systolic Blood Pressure in mm/Hg
#'     \item \code{cvd} Cardiovascular disesase based on extraction from patient billing codes. Y/N
#'   }
#'
#' There is a subset of patients that include genetic covariate information called \code{cvd_genodata}.
#'
#'  \itemize{
#'   \item \code{rs10757278} SNP data
#'   \item \code{rs1333049} SNP data
#'   \item \code{rs4665058} SNP data
#'   \item \code{rs8055236} SNP data
#'  }
#'
#' @docType data
#' @name cvd_patient
#' @aliases cvd_genodata
#' @usage data(cvd_patient)
#' @format
#'   a data frame with variables related to cvd risk. \code{cvd_genodata} is a smaller subset
#'   of the data with a few genetic cohorts.
#' @examples
#' #load full dataset
#' data(cvd_patient)
#'
#' #look at summary of data
#' summary(cvd_patient)
#' 
#' #load genotype dataset
#' data(cvd_genodata)
#' summary(cvd_genodata)
"cvd_patient"

#' CVD risk synthetic dataset
#'
#' A bayesian network for generating categorical synthetic data for assessing cardiovascular risk. 
#' Variable types are as follows:
#' 
#'   \itemize{
#'     \item \code{age} Patient Age Category. Age category of patient. string of age ranges.
#` Note that upper bound is not inclusive}
#'     \item \code{htn} Does patient have hypertension? Threshold systolic blood pressure is 150. Y/N
#'     \item \code{treat} Is patient receiving hypertension treatment? Y/N
#'     \item \code{smoking} Y/N based on threshold of pack years: 10
#'     \item \code{race} Race based on self-defined question in survey. AmInd (american indian),
#'     Asian/PI (asian/pacific islander), Black/AfAm (Black/African American), White
#'     \item \code{gender} Gender of patient. Male, Female, NA means that patient did not want gender recorded.
#'     \item \code{t2d} Whether patient has Type 2 diabetes. Y/N.
#'     \item \code{bmi} Body Mass Index of Patient. kg/m^2
#'     \item \code{sbp} Systolic Blood Pressure in mm/Hg
#'   \item \code{rs10757278} SNP data. Associated with race and total cholesterol.
#'   \item \code{rs1333049} SNP data. Associated with race and total cholesterol. Always co-occurs with rs10757278.
#'   \item \code{rs4665058} SNP data. Associated with race and total cholesterol.
#'   \item \code{rs8055236} SNP data. Variant is associated with increased risk.
#'   }
#' Note that not all covariates (including cardiovascular risk) were generated by the dataset.
#' Further details about how to generate the entire dataset from this network can be found from
#' \code{generate_data_from_network} in the vignettes folder.
#' @docType data
#' @name cvd_bayes_net
#' @usage data(cvd_bayes_net)
#' @format
#'   A Bayesian Network of class \code{CPTgrain} using the \code{gRain} package for representing the data.
#' @source
#' @examples
#' library(gRain)
#' data(cvd_bayes_net)
#'
#' #generate categorical data for 1000 patients
#' testData <- simulate(cvd_bayes_net, nsim =1000)
#' summary(testData)
"cvd_bayes_net"