title: Simple bootstrap statistical inference using the SAS system.
abstract: Nonparametric bootstrap statistical inference is a robust computer intensive method for generating estimates of statistical variability for which formulae are not known or asymptotic assumptions are not met. A SAS macro that implements simple nonparametric bootstrap statistical inference is presented with an example. The program code is easily generalized to any SAS procedure which includes a BY statement, and to cases of clustered data.
authors.affiliation: Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02215, USA. scole@rics.bwh.harvard.edu
authors.forename: S R
authors.initials: SR
authors.lastname: Cole
mesh_terms: D003627:Data Interpretation, Statistical; D006801:Humans; D009103:Multiple Sclerosis / Q000097:blood / Q000276:immunology; D012984:Software