Imports: Biostrings, protr,Peptides, kernlab, e1071

Title: Predictive Approaches in Psychology
Recent years have seen an increased interest in novel methods
for analyzing quantitative data from experimental psychology. Currently, however, they lack an
established and accessible software framework. Many existing implementations provide no guidelines,
consisting of small code snippets, or sets of packages. In addition, the use of existing packages
often requires advanced programming experience. 'PredPsych' is a user-friendly toolbox based on
machine learning predictive algorithms. It comprises of multiple functionalities for multivariate
analyses of quantitative behavioral data based on machine learning models.
Imports: plyr, ggplot2, caret, rpart, e1071, mclust, MASS, party,

Package: PredictABEL
Title: Assessment of risk prediction models
Version: 1.1
Date: 2011-02-09
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 (>= 2.9.0), 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.
License: GPL (>= 2)
Collate: 'PredictABEL.R'
Packaged: 2011-02-09 22:03:36 UTC; lennart
Repository: CRAN
Date/Publication: 2011-02-10 08:22:15