In microarray studies, an important problem is to compare a predictor of disease outcome derived from gene expression levels to standard clinical predictors. Comparing them on the same dataset that was used to derive the microarray predictor can lead to results strongly biased in favor of the...

Classical statistical theory ignores model selection in assessing estimation accuracy. Here we consider bootstrap methods for computing standard errors and confidence intervals that take model selection into account. The methodology involves bagging, also known as bootstrap smoothing, to tame...

Since Stein's original proposal in 1962, a series of papers have constructed confidence regions of smaller volume than the standard spheres for the mean vector of a multivariate normal distribution. A general approach to this problem is developed here and used to calculate a lower bound on the...