2
Simulate the use of personal checks in the US

Does anyone write paper checks anymore? According to researchers at the Federal Reserve Bank of Atlanta (Greene, et al., 2020), the use of paper checks has declined 63% among US consumers since the year 2000. The researchers surveyed more than 3,000 consumers in 2017-2018 and discovered that only 7% of

5
Generate random uniform points on an ellipse

I have previously written about how to efficiently generate points uniformly at random on the surface of a sphere. The method uses a mathematical fact from multivariate statistics: If X is drawn from the uncorrelated multivariate normal distribution, then S = X / ||X|| has the uniform distribution on the

0
Bootstrap predicted means by using PROC GLMSELECT

A previous article shows how to use the MODELAVERAGE statement in PROC GLMSELECT in SAS to perform a basic bootstrap analysis of the regression coefficients and fit statistics. A colleague asked whether PROC GLMSELECT can construct bootstrap confidence intervals for the predicted mean in a regression model, as described in

1
A simple way to bootstrap linear regression models in SAS

I've written many articles about bootstrapping in SAS, including several about bootstrapping in regression models. Many of the articles use a very general bootstrap method that can bootstrap almost any statistic that SAS can compute. The method uses PROC SURVEYSELECT to generate B bootstrap samples from the data, uses the

0
Add Unicode symbols and format text labels in SAS

It has been more than a decade since SAS 9.3 changed the default ODS destination from the old LISTING destination to more modern destinations such as HTML. One of the advantages of modern output destinations is support for Unicode symbols, superscripts, subscripts, and for formatting text by using boldface, italics,

2
Bootstrap confidence intervals for the predicted mean in a regression model

In ordinary least squares regression, there is an explicit formula for the confidence limit of the predicted mean. That is, for any observed value of the explanatory variables, you can create a 95% confidence interval (CI) for the predicted response. This formula assumes that the model is correctly specified and