The DO Loop
Statistical programming in SAS with an emphasis on SAS/IML programs![5 tips for customizing legends in PROC SGPLOT in SAS](https://blogs.sas.com/content/iml/files/2018/11/legendTip5-640x336.png)
When a graph includes several markers or line styles, it is often useful to create a legend that explains the relationship between the data and the symbols, color, and line styles in the graph. The SGPLOT procedure does a good job of automatically creating and placing a legend for most
![Singular parameterizations, generalized inverses, and regression estimates](https://blogs.sas.com/content/iml/files/2018/11/ginv8.png)
I remember the first time I used PROC GLM in SAS to include a classification effect in a regression model. I thought I had done something wrong because the parameter estimates table was followed by a scary-looking note: Note: The X'X matrix has been found to be singular, and a
![A funnel plot for immunization rates](https://blogs.sas.com/content/iml/files/2018/11/funnelimmun1-643x336.png)
Last week my colleague, Robert Allison, visualized data regarding immunization rates for kindergarten classes in North Carolina. One of his graphs was a scatter plot that displayed the proportion of unimmunized students versus the size of the class for 1,885 kindergarten classes in NC. This scatter plot is the basis
![Generalized inverses for matrices Graph of norm of solutions to the singular system A*b=c. The norm is plotted for vectors b + alpha*x_Null where b is the Moore-Penrose solution and x_Null is a basis for the nullspace of A.](https://blogs.sas.com/content/iml/files/2018/11/ginv1-640x336.png)
A data analyst asked how to compute parameter estimates in a linear regression model when the underlying data matrix is rank deficient. This situation can occur if one of the variables in the regression is a linear combination of other variables. It also occurs when you use the GLM parameterization
![Select ODS tables by using wildcards and regular expressions in SAS](https://blogs.sas.com/content/iml/files/2018/11/ODSSelectWhere1-427x336.png)
You might know that you can use the ODS SELECT statement to display only some of the tables and graphs that are created by a SAS procedure. But did you know that you can use a WHERE clause on the ODS SELECT statement to display tables that match a pattern?
![Create and compare ROC curves for any predictive model](https://blogs.sas.com/content/iml/files/2018/11/ROCOutside3-480x336.png)
An ROC curve graphically summarizes the tradeoff between true positives and true negatives for a rule or model that predicts a binary response variable. An ROC curve is a parametric curve that is constructed by varying the cutpoint value at which estimated probabilities are considered to predict the binary event.