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'.
| Version: |
1.1-0 |
| Depends: |
R (≥ 2.8), mboost (≥ 2.0-0), survival |
| Published: |
2012-10-29 |
| Author: |
Anne-Laure Boulesteix,
Torsten Hothorn. |
| Maintainer: |
Anne-Laure Boulesteix <boulesteix at ibe.med.uni-muenchen.de> |
| License: |
GPL (≥ 2) |
| NeedsCompilation: |
no |
| In views: |
Survival |
| CRAN checks: |
globalboosttest results |
Downloads: