The Benjamini--Hochberg method with infinitely many contrasts in linear models

Benjamini and Hochberg's method for controlling the false discovery rate is applied to the problem of testing infinitely many contrasts in linear models. Exact, easily calculated critical values are derived, defining a new multiple comparisons method for testing contrasts in linear models. The method is adaptive, depending on the data through the F-statistic, like the Waller--Duncan Bayesian multiple comparisons method. Comparisons with Scheffé's method are given, and the method is extended to the simultaneous confidence intervals of Benjamini and Yekutieli. Copyright 2008, Oxford University Press.