FOCUS AREAS

Our Favorite Things — in the 13.1 Releases

If you live in the United States and have any awareness of television programming, you know that a live presentation of The Sound of Music, with its famous song "My Favorite Things," was shown on NBC in December 2013. It produced a little confusion, because this version was based on the original Broadway production and not the popular film. But folks at SAS have absolutely no confusion about their favorite things in the 13.1 analytical releases!

Here are some favorite things from the Analytical Development staff:

Rick Wicklin, Principal Research Statistician Developer
Matrix heat maps in SAS/IML®

"They allow you to visualize the structure of large matrices."

Rob Pratt, Senior R&D Manager
COFOR loop in the OPTMODEL procedure

"It allows you to solve independent optimization problems in parallel with minimal syntax changes."

Warren Kuhfeld, R&D Director
New options for modifying the Kaplan-Meier survival plot

"They allow you to display patient-at-risk tables inside or outside the graph, as well as easily add an event table."

Fang Chen, Senior R&D Manager
Multithreading in the MCMC procedure

"This can often improve performance."

Patrick Hall, Research Statistician Developer
SAS® Enterprise Miner R integration

"It allows you to try your hand with new and experimental algorithms available in the R language."

Of course, if you know some of these people, you realize that they are touting their own work.

Which is fine, but we decided to look outside the confines of the development staff.

Mike Vorburger, Systems Engineer
BCHOICE procedure

"I am already a big fan of choice studies. Having the ability to design and analyze these studies within a Bayesian framework is a great big cherry on top, and I am excited!"

Udo Sglavo, Principal Analytical Consultant
SAS® Forecast Server 13.1

"Its seamless integration with SAS® Grid Manager makes it easy to distribute and manage workload to a grid of computing engines."

Funda Güneş, Research Statistician
MNAR statement in the MI procedure

"This new statement facilitates sensitivity analysis. Accounting for missing data correctly is really important, and SAS is providing more and more tools for analyzing missing data."

Jill Tao, Principal Technical Support Statistician
Power and sample size for GLM-type repeated measurements analyses

"I really like this new capability in PROC GLMPOWER. It's a great addition that will satisfy many people."

And then we have those people who simply couldn't pick just one favorite new feature. After all, the song is about a few of my favorite things!

Catherine Truxillo, Education Manager
IRT procedure

"It makes it so easy to fit item response theory models, and not just the classics. Testing and evaluation researchers have used macros in SAS to fit models for many years. PROC IRT will make life a little easier for many of our users."

Path diagrams in the CALIS procedure

"They add one more level of interpretability to the already extensive set of modeling languages in the CALIS procedure for expressing a structural equation model. The PATHDIAGRAM statement is versatile and the syntax is easy to use."

Kathleen Kiernan, Senior Principal Technical Support Statistician
Tweedie distribution

"I like having this distribution available in the GENMOD procedure. It's been highly requested."

Weighted multilevel models in the GLIMMIX procedure

"We've had requests for these for some time."

Kenneth Sanford, Senior Research Statistician
Access to FRED data

"I like having the access engine to the Federal Reserve Economic Data (FRED) in SAS/ETS®. It allows you to dynamically extract data from its source."

Censored regression with endogenous variables in the QLIM procedure

"Consistent estimates of coefficients can be generated."