Simple bootstrap statistical inference using the SAS system.
S. Cole. Computer methods and programs in biomedicine, 60 (1):
79-82(July 1999)3751<m:linebreak></m:linebreak>Resampling.
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.
%0 Journal Article
%1 Cole1999
%A Cole, S R
%D 1999
%J Computer methods and programs in biomedicine
%K DataInterpretation Humans MultipleSclerosis MultipleSclerosis:blood MultipleSclerosis:immunology Software Statistical
%N 1
%P 79-82
%T Simple bootstrap statistical inference using the SAS system.
%U http://www.ncbi.nlm.nih.gov/pubmed/10430465
%V 60
%X 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.
@article{Cole1999,
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.},
added-at = {2023-02-03T11:44:35.000+0100},
author = {Cole, S R},
biburl = {https://www.bibsonomy.org/bibtex/24938e10cb68ece063052185a2fa53ed2/jepcastel},
interhash = {b1220865e2563f4f7bf512f493ece995},
intrahash = {4938e10cb68ece063052185a2fa53ed2},
issn = {0169-2607},
journal = {Computer methods and programs in biomedicine},
keywords = {DataInterpretation Humans MultipleSclerosis MultipleSclerosis:blood MultipleSclerosis:immunology Software Statistical},
month = {7},
note = {3751<m:linebreak></m:linebreak>Resampling},
number = 1,
pages = {79-82},
pmid = {10430465},
timestamp = {2023-02-03T11:44:35.000+0100},
title = {Simple bootstrap statistical inference using the SAS system.},
url = {http://www.ncbi.nlm.nih.gov/pubmed/10430465},
volume = 60,
year = 1999
}