The DO Loop
Statistical programming in SAS with an emphasis on SAS/IML programs
This article shows how to construct a butterfly plot in SAS. A butterfly plot (also called a butterfly chart) is a comparative bar chart or histogram that displays the distribution of a variable for two subpopulations. A butterfly plot for the cholesterol readings of 5,057 patients in a medical study
In a recent blog post, Chris Hemedinger used a scatter plot to show the result of 100 coin tosses. Chris arranged the 100 results in a 10 x 10 grid, where the first 10 results were shown on the first row, the second 10 were shown on the second row, and so
In my article about how to construct calibration plots for logistic regression models in SAS, I mentioned that there are several popular variations of the calibration plot. The previous article showed how to construct a loess-based calibration curve. Austin and Steyerberg (2013) recommend the loess-based curve on the basis of
A logistic regression model is a way to predict the probability of a binary response based on values of explanatory variables. It is important to be able to assess the accuracy of a predictive model. This article shows how to construct a calibration plot in SAS. A calibration plot is
In a previous blog post, I discussed ways to produce statistically independent samples from a random number generator (RNG). The best way is to generate all samples from one stream. However, if your program uses two or more SAS DATA steps to simulate the data, you cannot use the same
Simulation studies require both randomness and reproducibility, two qualities that are sometimes at odds with each other. A Monte Carlo simulation might need to generate millions of random samples, where each sample contains dozens of continuous variables and many thousands of observations. In simulation studies, the researcher wants each sample