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On using the bootstrap for multiple comparisons
1Department of ISQS, Texas Tech University, Lubbock, Texas 79409-2101, USA. peter.westfall@ttu.edu
Abstract:
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.
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