Rick Wicklin, PhD, is a distinguished researcher in computational statistics at SAS and is a principal developer of SAS/IML software. His areas of expertise include computational statistics, simulation, statistical graphics, and modern methods in statistical data analysis. Rick is author of the books Statistical Programming with SAS/IML Software and Simulating Data with SAS.
I am not a big fan of the macro language, and I try to avoid it when I write SAS/IML programs. I find that the programs with many macros are hard to read and debug. Furthermore, the SAS/IML language supports loops and indexing, so many macro constructs can be replaced
A regular reader noticed my post on initializing vectors by using repetition factors and asked whether that technique would be useful to expand data that are given in value-frequency pairs. The short answer is "no." Repetition factors are useful for defining (static) matrix literals. However, if you want to expand
In a previous blog post, I described how to use a spread plot to compare the distributions of several variables. Each spread plot is a graph of centered data values plotted against the estimated cumulative probability. Thus, spread plots are similar to a (rotated) plot of the empirical cumulative distribution
Suppose that you have several data distributions that you want to compare. Questions you might ask include "Which variable has the largest spread?" and "Which variables exhibit skewness?" More generally, you might be interested in visualizing how the distribution of one variable differs from the distribution of other variables. The
Last week I showed how to use simulation to estimate the power of a statistical test. I used the two-sample t test to illustrate the technique. In my example, the difference between the means of two groups was 1.2, and the simulation estimated a probability of 0.72 that the t
A SAS user told me that he computed a vector of values in the SAS/IML language and wanted to use those values on a statement in a SAS procedure. The particular application involved wanting to use the values on the ESTIMATE and CONTRAST statements in a SAS regression procedure, but
The power of a statistical test measures the test's ability to detect a specific alternate hypothesis. For example, educational researchers might want to compare the mean scores of boys and girls on a standardized test. They plan to use the well-known two-sample t test. The null hypothesis is that the
Has anyone noticed that the REG procedure in SAS/STAT 12.1 produces heat maps instead of scatter plots for fit plots and residual plots when the regression involves more than 5,000 observations? I wasn't aware of the change until a colleague informed me, although the change is discussed in the "Details"
In my article "Simulation in SAS: The slow way or the BY way," I showed how to use BY-group processing rather than a macro loop in order to efficiently analyze simulated data with SAS. In the example, I analyzed the simulated data by using PROC MEANS, and I use the
Last week I discussed a program that had three nested loops that used scalar operations in the innermost loop. I mentioned that this program was not vectorized, and would therefore be slow in a matrix language such as SAS/IML, MATLAB, or R. I then went through a series of steps
