Assessment of Risk Prediction Models
An example code to construct a risk model using logistic regression an...
Function to fit a logistic regression model.
Function to obtain multivariate odds ratios from a logistic regression...
Function for calibration plot and Hosmer-Lemeshow goodness of fit test...
Function for box plots of predicted risks separately for individuals w...
Function for predictiveness curve.
Function to plot posterior risks against prior risks.
Function to plot histogram of risks separated for individuals with and...
Function to plot predicted risks against risk scores.
Function for a receiver operating characteristic curve (ROC) plot and ...
An R package for the analysis of (genetic) risk prediction studies.
Function to compute predicted risks for all individuals in the dataset...
Function for reclassification table and statistics.
Function to compute genetic risk scores.
Function to construct a simulated dataset containing individual genoty...
We included functions to assess the performance of risk models. The package contains functions for the various measures that are used in empirical studies, including univariate and multivariate odds ratios (OR) of the predictors, the c-statistic (or area under the receiver operating characteristic (ROC) curve (AUC)), Hosmer-Lemeshow goodness of fit test, reclassification table, net reclassification improvement (NRI) and integrated discrimination improvement (IDI). Also included are functions to create plots, such as risk distributions, ROC curves, calibration plot, discrimination box plot and predictiveness curves. In addition to functions to assess the performance of risk models, the package includes functions to obtain weighted and unweighted risk scores as well as predicted risks using logistic regression analysis. These logistic regression functions are specifically written for models that include genetic variables, but they can also be applied to models that are based on non-genetic risk factors only. Finally, the package includes function to construct a simulated dataset with genotypes, genetic risks, and disease status for a hypothetical population, which is used for the evaluation of genetic risk models.