PredictABEL includes 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 cstatistic (or area under the receiver operating characteristic (ROC) curve (AUC)), HosmerLemeshow 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 nongenetic 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.
Package details 


Author  Suman Kundu, Yurii S. Aulchenko, A. Cecile J.W. Janssens 
Date of publication  20130906 14:31:39 
Maintainer  Suman Kundu <s.kundu@erasmusmc.nl> 
License  GPL (>= 2) 
Version  1.22 
URL  http://www.genabel.org/packages/PredictABEL 
Package repository  View on RForge 
Installation 
Install the latest version of this package by entering the following in R:

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