On using the bootstrap for multiple comparisons.
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.
Department of ISQS, Texas Tech University, Lubbock, Texas 79409-2101, USA. peter.westfall@ttu.edu
Peter H
PH
Westfall
D000818:Animals; D003627:Data Interpretation, Statistical; D016208:Databases, Factual / Q000706:statistics & numerical data*; D051379:Mice; D018709:Statistics, Nonparametric