globalboosttest: Testing the additional predictive value of high-dimensional data

'globalboosttest' implements a permutation-based testing procedure to globally test the (additional) predictive value of a large set of predictors given that a small set of predictors is already available. Currently, 'globalboosttest' supports binary outcomes (via logistic regression) and survival outcomes (via Cox regression). It is based on boosting regression as implemented in the package 'mboost'.

AuthorAnne-Laure Boulesteix <boulesteix@ibe.med.uni-muenchen.de>, Torsten Hothorn <torsten.hothorn@stat.uni-muenchen.de>.
Date of publication2012-10-29 08:58:54
MaintainerAnne-Laure Boulesteix <boulesteix@ibe.med.uni-muenchen.de>
LicenseGPL (>= 2)
Version1.1-0

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Files in this package

globalboosttest
globalboosttest/data
globalboosttest/data/simdatabin.RData
globalboosttest/data/simdatasurv.RData
globalboosttest/NAMESPACE
globalboosttest/man
globalboosttest/man/simdatabin.Rd globalboosttest/man/globalboosttest.Rd globalboosttest/man/globalboosttest-internal.Rd globalboosttest/man/simdatasurv.Rd
globalboosttest/DESCRIPTION
globalboosttest/MD5
globalboosttest/R
globalboosttest/R/globalboosttest.r

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