A study of pre-validation
| dc.creator | Höfling, Holger | |
| dc.creator | Tibshirani, Robert | |
| dc.date | 2008-07-25 | |
| dc.date.accessioned | 2026-07-07T09:52:56Z | |
| dc.date.available | 2026-07-07T09:52:56Z | |
| dc.description | Given a predictor of outcome derived from a high-dimensional dataset, pre-validation is a useful technique for comparing it to competing predictors on the same dataset. For microarray data, it allows one to compare a newly derived predictor for disease outcome to standard clinical predictors on the same dataset. We study pre-validation analytically to determine if the inferences drawn from it are valid. We show that while pre-validation generally works well, the straightforward "one degree of freedom" analytical test from pre-validation can be biased and we propose a permutation test to remedy this problem. In simulation studies, we show that the permutation test has the nominal level and achieves roughly the same power as the analytical test. | |
| dc.description | Published in at http://dx.doi.org/10.1214/07-AOAS152 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Institute of Mathematical Statistics (http://www.imstat.org) | |
| dc.identifier | https://arxiv.org/abs/0807.4105 | |
| dc.identifier | http://arxiv.org/abs/0807.4105 | |
| dc.identifier | Annals of Applied Statistics 2008, Vol. 2, No. 2, 643-664 | |
| dc.identifier | doi:10.1214/07-AOAS152 | |
| dc.identifier.uri | http://salesiana.dossiersoluciones.com/handle/123456789/165776 | |
| dc.subject | Applications | |
| dc.title | A study of pre-validation | |
| dc.type | text |