# Posts Tagged ‘ Bootstrap and Resampling ’

## The essential guide to bootstrapping in SAS

December 12, 2018
By

This article describes best practices and techniques that every data analyst should know before bootstrapping in SAS. The bootstrap method is a powerful statistical technique, but it can be a challenge to implement it efficiently. An inefficient bootstrap program can take hours to run, whereas a well-written program can give

Tags: ,
Posted in SAS | Comments Off on The essential guide to bootstrapping in SAS

## Bootstrap regression estimates: Residual resampling

October 29, 2018
By

If you want to bootstrap the parameters in a statistical regression model, you have two primary choices. The first, case resampling, is discussed in a previous article. This article describes the second choice, which is resampling residuals (also called model-based resampling). This article shows how to implement residual resampling in

Tags: ,
Posted in SAS | Comments Off on Bootstrap regression estimates: Residual resampling

## Bootstrap regression estimates: Case resampling

October 24, 2018
By

If you want to bootstrap the parameters in a statistical regression model, you have two primary choices. The first is case resampling, which is also called resampling observations or resampling pairs. In case resampling, you create the bootstrap sample by randomly selecting observations (with replacement) from the original data. The

Tags: ,
Posted in SAS | Comments Off on Bootstrap regression estimates: Case resampling

## How to use the %BOOT and %BOOTCI macros in SAS

July 23, 2018
By

Since the late 1990s, SAS has supplied macros for basic bootstrap and jackknife analyses. This article provides an example that shows how to use the %BOOT and %BOOTCI macros. The %BOOT macro generates a bootstrap distribution and computes basic statistics about the bootstrap distribution, including estimates of bias, standard error,

Tags: ,
Posted in SAS | Comments Off on How to use the %BOOT and %BOOTCI macros in SAS

## Balanced bootstrap resampling in SAS

July 18, 2018
By

This article shows how to implement balanced bootstrap sampling in SAS. The basic bootstrap samples with replacement from the original data (N observations) to obtain B new samples. This is called "uniform" resampling because each observation has a uniform probability of 1/N of being selected at each step of the

Tags: ,
Posted in SAS | Comments Off on Balanced bootstrap resampling in SAS

## The bootstrap method in SAS: A t test example

June 20, 2018
By

A previous article provides an example of using the BOOTSTRAP statement in PROC TTEST to compute bootstrap estimates of statistics in a two-sample t test. The BOOTSTRAP statement is new in SAS/STAT 14.3 (SAS 9.4M5). However, you can perform the same bootstrap analysis in earlier releases of SAS by using

Tags: , ,
Posted in SAS | Comments Off on The bootstrap method in SAS: A t test example

## The BOOTSTRAP statement for t tests in SAS

June 18, 2018
By

Bootstrap resampling is a powerful way to estimate the standard error for a statistic without making any parametric assumptions about its sampling distribution. The bootstrap method is often implemented by using a sequence of calls to resample from the data, compute a statistic on each sample, and analyze the bootstrap

Tags: , ,
Posted in SAS | Comments Off on The BOOTSTRAP statement for t tests in SAS

## Sample and obtain the results in random order

June 6, 2018
By

The SURVEYSELECT procedure in SAS 9.4M5 supports the OUTRANDOM option, which causes the selected items in a simple random sample to be randomly permuted after they are selected. This article describes several statistical tasks that benefit from this option, including simulating card games, randomly permuting observations in a DATA step,

Tags: , ,
Posted in SAS | Comments Off on Sample and obtain the results in random order

## Welcome!

SAS-X.com offers news and tutorials about the various SAS® software packages, contributed by bloggers. You are welcome to subscribe to e-mail updates, or add your SAS-blog to the site.