Simple bootstrap statistical inference using the SAS system

被引：25

作者：

Cole, SR ^{[1
]}

机构：

[1] Harvard Univ, Sch Med, Brigham & Womens Hosp, Div Prevent Med, Boston, MA 02215 USA

来源：

COMPUTER METHODS AND PROGRAMS IN BIOMEDICINE | 1999年 / 60卷 / 01期

关键词：

bootstrap; resampling statistics; SAS macro;

D O I：

10.1016/S0169-2607(99)00016-4

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

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. (C) 1999 Elsevier Science Ireland Ltd. All rights reserved.

引用

页码：79 / 82

页数：4

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