A SAS programmer recently asked me how to compute a kernel regression in SAS. He had read my blog posts "What is loess regression" and "Loess regression in SAS/IML" and was trying to implement a kernel regression in SAS/IML as part of a larger analysis. This article explains how to
Tag: Statistical Programming
A SAS programmer recently asked how to interpret the "standardized regression coefficients" as computed by the STB option on the MODEL statement in PROC REG and other SAS regression procedures. The SAS documentation for the STB option states, "a standardized regression coefficient is computed by dividing a parameter estimate by
Video killed the radio star.... We can't rewind, we've gone too far. -- The Buggles (1979) "You kids have it easy," my father used to tell me. "When I was a kid, I didn't have all the conveniences you have today." He's right, and I could say the same
The SGPLOT procedure in SAS makes it easy to create graphs that overlay various groups in the data. Many statements support the GROUP= option, which specifies that the graph should overlay group information. For example, you can create side-by-side bar charts and box plots, and you can overlay multiple scatter
This article shows how to score (evaluate) a quantile regression model on new data. SAS supports several procedures for quantile regression, including the QUANTREG, QUANTSELECT, and HPQUANTSELECT procedures. The first two procedures do not support any of the modern methods for scoring regression models, so you must use the "missing
When you use a regression procedure in SAS that supports variable selection (GLMSELECT or QUANTSELECT), did you know that the procedures automatically produce a macro variable that contains the names of the selected variables? This article provides examples and details. A previous article provides an overview of the 'SELECT' procedures
This article describes how to obtain an initial guess for nonlinear regression models, especially nonlinear mixed models. The technique is to first fit a simpler fixed-effects model by replacing the random effects with their expected values. The parameter estimates for the fixed-effects model are often good initial guesses for the
When you fit nonlinear fixed-effect or mixed models, it is difficult to guess the model parameters that fit the data. Yet, most nonlinear regression procedures (such as PROC NLIN and PROC NLMIXED in SAS) require that you provide a good guess! If your guess is not good, the fitting algorithm,
A previous article provides an example of using the BOOTSTRAP statement in PROC TTEST to compute bootstrap estimates of statistics in a two-sample t test. The BOOTSTRAP statement is new in SAS/STAT 14.3 (SAS 9.4M5). However, you can perform the same bootstrap analysis in earlier releases of SAS by using
I recently recorded a short video about the new syntax for specifying and manipulating lists in SAS/IML 14.3. This is a video of my Super Demo at SAS Global Forum 2018. The new syntax supports dynamic arrays, associative arrays ("named lists"), and hierarchical data structures such as lists of lists.