{Reference Type}: Journal Article
{Title}: Rotation-based multiple testing in the multivariate linear model.
{Author}: Solari A;Finos L;Goeman JJ;
{Journal}: Biometrics
{Volume}: 70
{Issue}: 4
{Year}: Dec 2014
{Factor}: 1.701
{DOI}: 10.1111/biom.12238
{Abstract}: In observational microarray studies, issues of confounding invariably arise. One approach to account for measured confounders is to include them as covariates in a multivariate linear model. For this model, however, the application of permutation-based multiple testing procedures is problematic because exchangeability of responses, in general, does not hold. Nevertheless, it is possible to achieve rotatability of transformed responses at the cost of a distributional assumption. We argue that rotation-based multiple testing, by allowing for adjustments for confounding, represents an important extension of permutation-based multiple testing procedures. The proposed methodology is illustrated with a microarray observational study on breast cancer tumors. Software to perform the procedure described in this article is available in the flip R package.