A study of pre-validation

Details A study of pre-validation A study of pre-validation

2008-07-25

arxiv.org/abs/0807.4105v1

Annals of Applied Statistics 2008, Vol. 2, No. 2, 643-664

Statistics

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Published in at http://dx.doi.org/10.1214/07-AOAS152 the Annals of Applied Statistics (http://www.imstat.org/aoas/) by the Ins

Scientific paper

10.1214/07-AOAS152

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.

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