Simple bootstrap statistical inference using the SAS system. |
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| Authors: | S R Cole |
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| Affiliation: | Division of Preventive Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA 02215, USA. scole@rics.bwh.harvard.edu |
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| 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. |
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