R: Assessment of risk prediction models

Assessment of risk prediction models

Documentation for package ‘PredictABEL’ version 1.2

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PredictABEL-package An R package for the analysis of (genetic) risk prediction studies.
ExampleData A hypothetical dataset that is used to demonstrate all functions.
ExampleModels An example code to construct a risk model using logistic regression analysis.
fitLogRegModel Function to fit a logistic regression model.
ORmultivariate Function to obtain multivariate odds ratios from a logistic regression model.
ORunivariate Function to compute univariate ORs for genetic predictors.
plotCalibration Function for calibration plot and Hosmer-Lemeshow goodness of fit test.
plotDiscriminationBox Function for box plots of predicted risks separately for individuals with and without the outcome of interest.
plotPredictivenessCurve Function for predictiveness curve.
plotPriorPosteriorRisk Function to plot posterior risks against prior risks.
plotRiskDistribution Function to plot histogram of risks separated for individuals with and without the outcome of interest.
plotRiskscorePredrisk Function to plot predicted risks against risk scores.
plotROC Function for a receiver operating characteristic curve (ROC) plot and area under the ROC curve (AUC) value.
predRisk Function to compute predicted risks for all individuals in the dataset.
reclassification Function for reclassification table and statistics.
riskScore Function to compute genetic risk scores.
simulatedDataset Function to construct a simulated dataset containing individual genotype data, estimated genetic risk and disease status.