About this blog
Rick Wicklin, PhD, is a distinguished researcher in computational statistics at SAS and is a principal developer of PROC IML and SAS/IML Studio. This blog focuses on statistical programming. It discusses statistical and computational algorithms, statistical graphics, simulation, efficiency, and data analysis. Rick is author of the books Statistical Programming with SAS/IML Software and Simulating Data with SAS.
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Do you want to create customized SAS graphs by using PROC SGPLOT and the other ODS graphics procedures? An essential skill that you need to learn is how to merge, join, append, and concatenate SAS data sets that come from different sources. The SAS statistical graphics procedures (SG procedures) enable […]Post a Comment
Every year near Halloween I write an article in which I demonstrate a simple programming trick that is a real treat to use. This year's trick (which features the CMISS function and the crossproducts matrix in SAS/IML) enables you to count the number of observations that are missing for pairs […]Post a Comment
Graphs enable you to visualize how the predicted values for a regression model depend on the model effects. You can gain an intuitive understanding of a model by using the EFFECTPLOT statement in SAS to create graphs like the one shown at the top of this article. Many SAS regression […]Post a Comment
I got several positive comments about a recent tip, "How to fit a variety of logistic regression models in SAS." A reader asked if I knew any other similar resources about statistical analysis in SAS. Absolutely! One gem that comes to mind is "Examples of writing CONTRAST and ESTIMATE statements." […]Post a Comment
Optimization is a primary tool of computational statistics. SAS/IML software provides a suite of nonlinear optimizers that makes it easy to find an optimum for a user-defined objective function. You can perform unconstrained optimization, or define linear or nonlinear constraints for constrained optimization. Over the years I have seen many […]Post a Comment
SAS programmers sometimes ask, "How do I create a design matrix in SAS?" A design matrix is a numerical matrix that represents the explanatory variables in regression models. In simple models, the design matrix contains one column for each continuous variable and multiple columns (called dummy variables) for each classification […]Post a Comment
Last week Sanjay Matange wrote about a new SAS 9.4m3 option that enables you to show all categories in a graph legend, even when the data do not contain all the categories. Sanjay's example was a chart that showed medical conditions classified according to the scale "Mild," "Moderate," and "Severe." […]Post a Comment
A common question on SAS discussion forums is how to compute a moving average in SAS. This article shows how to use PROC EXPAND and contains links to articles that use the DATA step or macros to compute moving averages in SAS. In a previous post, I explained how to […]Post a Comment
Last week my colleague Chris Hemedinger published a blog post that described how to use the ODS LAYOUT GRIDDED statement to arrange tables and graphs in a panel. The statement was introduced in SAS 9.4m1 (December 2013). Gridded layout is supported for HTML, POWERPOINT, and the PRINTER family of destinations […]Post a Comment
Statistical programmers often need to evaluate complicated expressions that contain square roots, logarithms, and other functions whose domain is restricted. Similarly, you might need to evaluate a rational expression in which the denominator of the expression can be zero. In these cases, it is important to avoid evaluating a function […]Post a Comment