Package: PredictABEL
Title: Assessment of risk prediction models
Version: 1.2
Date: 2011-10-19
Author: Suman Kundu, Yurii S. Aulchenko, A. Cecile J.W. Janssens
Maintainer: Suman Kundu <s.kundu@erasmusmc.nl>, A. Cecile J.W. Janssens
        <a.janssens@erasmusmc.nl>
Depends: R (>= 2.12.0), Hmisc, ROCR, epitools, PBSmodelling
Suggests: GenABEL
Description: 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 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 that contains
        individual genotype data, estimated genetic risk, and disease
        status, used for the evaluation of genetic risk models.
License: GPL (>= 2)
Packaged: 2011-10-19 09:28:23 UTC; lennart
Repository: CRAN
Date/Publication: 2011-10-19 10:07:43