https://github.com/cran/PredictABEL
Tip revision: cdeccfc4d28ad013bbfb3f590589685935b1330d authored by Suman Kundu on 25 February 2020, 09:00:08 UTC
version 1.2-3
version 1.2-3
Tip revision: cdeccfc
DESCRIPTION
Package: PredictABEL
Title: Assessment of Risk Prediction Models
Version: 1.2-3
Date: 2020-02-17
Author: Suman Kundu, Yurii S. Aulchenko, A. Cecile J.W. Janssens
Maintainer: Suman Kundu <suman_math@yahoo.com>
Depends: R (>= 2.12.0)
Imports: Hmisc, ROCR, epitools, PBSmodelling, lazyeval, methods
Description: 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.
License: GPL (>= 2)
Packaged: 2020-02-24 19:09:45 UTC; kundus
NeedsCompilation: no
Repository: CRAN
Date/Publication: 2020-02-25 10:00:08 UTC
RoxygenNote: 7.0.2