I’m happy to announce that we are less than a week away from shipping the latest releases of analytical software from SAS. Please be on the lookout for the 14.2 releases of SAS/STAT^®, SAS/ETS^®, SAS/IML^®, SAS/OR^®, and other analytical products accompanying the fourth maintenance release of SAS^® 9.4. Here are highlights of these new releases: 

In addition, you will notice a new framework for the online documentation called the Help Center. Documentation such as the SAS/STAT User’s Guide now provides links to example code right in the “Examples” section, and the SAS/STAT documentation also provides easy access to videos that pertain to each chapter. See support.sas.com in a few weeks for more information. 

You may have heard about the new SAS analytics platform called SAS^® Viya™, which is open, built on high-performance computing, and designed for cloud use. You may want to learn about one of the first products released, SAS® Visual Data Mining and Machine. Bridges to SAS Viya from SAS 9.4M4 are available from SAS^® Enterprise Miner™ and SAS^® Studio.

In this newsletter, we highlight several SAS^® Global Forum papers from three professors who are popular speakers, introduce a number of new videos, and provide the usual technical tips.

As always, let us know what you think about our latest releases!

Maura Stokes

Senior R&D Director, Statistical Applications 

Technical Papers

Differencing a Time Series

Each night on the news we hear the level of the Dow Jones Industrial Average along with the “first difference,” which is today’s price-weighted average minus yesterday’s. It is that series of first differences that excites or depresses us each night, as it reflects whether stocks made or lost money that day. Furthermore, the differences form the data series that has the most addressable statistical features. In particular, the differences have the stationarity requirement, which justifies standard distributional results such as asymptotically normal distributions of parameter estimates. Differencing arises in many practical time series because they seem to have what are called “unit roots,” which mathematically indicate the need to take differences. In 1976, Dickey and Fuller developed the first well-known tests to decide whether differencing is needed. These tests are part of the ARIMA procedure in SAS/ETS in addition to many other time series analysis products. Professor Dave Dickey reviews a little of what it was like to do the development and the required computing back then, says a little about why this is an important issue, and focuses on examples.

Competing-Risks Analyses: Overview of Regression Models

Competing-risks analyses are methods for analyzing the time to a terminal event (such as death or failure) and its cause or type. The LIFETEST procedure provides for nonparametric estimation of the cumulative incidence function (CIF) from event times and their associated causes, allowing for right-censoring when the event and its cause are not observed. Cause-specific hazard functions that are derived from the CIFs are the analogs of the hazard function when only a single cause is present. Death by one cause precludes occurrence of death by any other cause, because an individual can die only once. Incorporating explanatory variables in hazard functions provides an approach to assessing their impact on overall survival and on the CIF. This semiparametric approach can be analyzed in the PHREG procedure. Professor Joseph Gardiner describes these techniques and their implementation with examples. 

PROC GLIMMIX as a Teaching and Planning Tool for Experiment Design

Graduate students and even relatively experienced statistical consultants can find translating a study design into a useful model to be a challenge. Generalized linear mixed models (GLMMs) complicate this challenge, because they accommodate complex designs, complex error structures, and non-Gaussian data. This paper covers strategies proven to be effective in design and modeling courses and consulting sessions. In addition, GLMM methods can be extremely useful in planning experiments. Professor Walter Stroup discusses methods to implement precision and power analysis to help choose between competing designs and to assess the adequacy of proposed designs.

Technical Highlights

SAS/STAT Users Still Moving to the SAS 9.4 Platform? 

If you are moving up to SAS 9.4 and would like to catch up on the recent SAS/STAT releases on that platform, this handout is for you! Get an overview of our new additions in missing data analysis, modern survival data analysis, statistical modeling, spatial point pattern analysis, Bayesian analysis, item response analysis, classification and regression trees, and performance enhancements. There’s truly something here for everyone. And if you aren’t currently on the move, feel free to use this handout however it helps you get into the passing lane!

Tech Support Points Out

Talks and Tutorials

Winter Simulation Conference

SAS/OR will highlight SAS® Simulation Studio at the Winter Simulation Conference, December 11–14 in Washington, DC. We will have an exhibit booth, and we will also present in the Vendor Track.