There are many ways to bootstrap data for multiple comparisons procedures. Methods described here include (i) bootstrap (parametric and nonparametric) as a generalization of classical normal-based MaxT methods, (ii) bootstrap as an approximation to exact permutation methods, (iii) bootstrap as a generator of realistic null data sets, and (iv) bootstrap as a generator of realistic non-null data sets. Resampling of MinP versus MaxT is discussed, and the use of the bootstrap for closed testing is also presented. Applications to biopharmaceutical statistics are given.