Category Archives: SAS User Groups

The Last NESUG

I attended NESUG 2013 in Burlington, VT earlier this week, along with some colleagues. One announcement at the end of opening session caught us off-guard – that NESUG 2013 was to be the last NESUG. NESUG 2014, which had been originally planned to take place in Philadephia, is now canceled, as are all other NESUG conferences going forward. The committee sent out a follow-up email to their opening session announcement in which they detailed the reasons for the announcement. SAS has been a major sponsor of the conference since its inception, contributing both funding support and a large number of displays and presenters to the conference. Apparently SAS notified the committee on August 29th that they have chosen to reduce funding for all the annual regional conferences, choosing instead to focus on industry-specific conferences such as PharmaSUG and more shorter, local events. Given this withdrawal of support, the committee determined that it could no longer hold the annual conference.

NESUG was the first of the regional conferences to be held this fall, so we are expecting news from some of the other regional conferences such as SESUG and WUSS later this fall as they decide whether they, too, will be unable to continue putting on their events. The regional conferences provided a cross-industry forum for users to gather locally and share programming techniques, discuss new procedures and SAS updates, and share their research projects with a tight-knit community. NESUG was a more intimate gathering than SAS Global Forum and for many first-time presenters, it was a smaller, less-intimidating conference, often within driving distance of home, at which to share their work. We will miss seeing the same faces year after year and are disappointed that SAS has decided to withdraw their support and seek another direction.

Updated: As of September 18th, the NESUG committee has posted more information on their site about their decision, along with some documents from SAS about their support of the regional conferences going forward.

SAS Withdraws Funding for Regional User Groups

At the opening session this week, the NESUG committee announced that NESUG 2013 would be the last NESUG. They sent a follow-up email the next day explaining the reasons behind this decision:

To the NESUG User Community:

On August 29, SAS informed us and the other regional user groups that they were significantly reducing funding support for annual regional conferences, including NESUG, beginning in 2014.

The NESUG Executive Committee met on September 3 to discuss this decision and to decide our response. We came to the conclusion that we, as volunteers, can no longer conduct a conference as successfully as we have for more than a quarter of a century. Therefore, the NESUG Executive Committee has voted unanimously to cancel all future conferences.

We want to thank our attendees, and especially the hundreds of volunteer presenters, session coordinators, registration desk volunteers, and others who so generously donated their time and talent to help the NESUG conference to set a standard of excellence for over a quarter of a century. We will miss you, but we encourage you to stay involved with the SAS community.

Regards,
NESUG Inc. “Of the user, by the user, for the user”

Daphne Ewing
Warren Stinson
Sue Douglass
Earl Westerlund
Lois Levin
Paul Gorrell
Lisa Eckler
Lisa Pyle
George Hurley

HASUG Meeting Notes: December 2012

HASUG’s 4th quarter meeting, featuring speakers Kevin Viel and Vinodh Paida, took place at Boehringer Ingelheim in Danbury, CT. PharmaSUG speaker Kevin Viel led with “Using the SAS System as a Bioinformatics Tool: A Macro That Calls the Standalone BLAST Setup”. Before sharing the macro, Viel began with some background on genomics and BLAST. A genome is all the genetic information about an organism; the human genome is the complete DNA of an individual person. DNA is a nucleic acid formed by a chain of nucleotides. These nucleotides are four possible bases (adenine, cytosine, guanine, and thymine) represented by A,C,T,G, or N for unknown. We are interested in the nucleotide sequences of DNA fragments (for example, AAAGTCTGAC), which can be used to identify genetic diseases in an individual or to find evolutionary relationships. Viel discussed four types of simple variations that can occur within a given nucleotide sequence: single substitution (AAAGTCTGAC vs. AAACTCCGAC), insertion (AAACTGCCGAC), deletion (AAAGTCTGAC vs. AAGTCTGAC), or inversion (AAAGTCTGAC vs. AAATGCTGAC).

Looking for similar sequences manually is a tedious, time-intensive process which can involve transcription errors. As an alternative, Viel discussed using regular expressions in SAS to look for matching sequences, allowing for one mismatching character such as a single nucleotide substitution in a strand. He then introduced a SAS macro to call BLAST, a sequence similarity tool from NCBI which can be downloaded or used interactively on the web. NCBI’s website defines the tool as follows: “The Basic Local Alignment Search Tool (BLAST) finds regions of local similarity between sequences. The program compares nucleotide or protein sequences to sequence databases and calculates the statistical significance of matches.” Viel also described how to set up BLAST for Windows PC and configure the necessary environmental variables for the program to run successfully.

Following Viel’s presentation, Vinodh Paida of Accenture/Octagon shared “Data Edit Checks Integration Using ODS Tagset”, applicable to SAS versions 9.1.3 or higher. Although the paper was written specifically with regard to clinical trials data and reporting, it can generalize easily to other types of data and domains. First Paida summarized five types of commonly encountered data issues centering around invalid dates and missing data in clinical trials: partial dosing start and stop dates (checked for with the length function), future dates, subject with final summary data but missing stop date, adverse events with missing terms, and lab data with missing units but available results.

His SAS code contained blocks of edit checks for each scenario, followed by a macro to create a multi-sheet Excel workbook including a TOC listing with the selected edit checks, along with corresponding descriptions and sheet names. Problem records for each edit check are then output in different sheets of the workbook. The code is flexible to allow the user to select which edit checks to output to Excel. This presentation reminded me of an earlier HASUG presentation which inspired my post on how to create a data dictionary in Excel.

BASUG Meeting Notes: September 2012

I attended the third quarter BASUG (Boston Area SAS User Group) meeting in Cambridge, MA at the Microsoft NERD center on September 20th. Morning speakers included Craig Dickstein of Tamarack Professional Services and Paul Gorrell of IMPAQ International. Craig Dickstein is one of the authors of Health Care Data and SAS and has worked with Cigna as a HEDIS code reviewer. An afternoon training on using SAS to analyze publicly available healthcare data sets was also led by Paul Gorrell.

The entire day focused on healthcare data, with the following presentations: “Data Hygiene Routines for Administrative Healthcare Data”, “Calculating the Hospital Readmission Interval”, and “Using SAS to Generate Estimates of U.S. Prescription Drug Cost and Use”. Dickstein’s presentation on “data hygiene routines” included a useful overview of the architecture of ICD-9 diagnosis codes, CPT codes (categories I-III), and HCPCS procedure codes. His code samples demonstrated how to create procedure code lookup tables with Proc Format and use these lookup tables to identify bad values. His second presentation described the challenges of calculating re-admission intervals and presented some alternatives to using the LAG function, including a detailed discussion of how the Program Data Vector (PDV) works in SAS. Finally, Paul Gorrell discussed how to replicate the numbers found in commonly cited statistics such as “5% of Americans make up 50% of U.S. health care spending” by using SAS/STAT survey procedures such as Proc Surveyfreq and Proc Surveymeans in combination with the HRQ data files available from the Medical Expenditure Panel Survey (MEPS). The next quarterly meeting is scheduled for December 11th, 2012.

UConn SAS Day

I attended a UConn SAS Day last week at the UConn School of Business Graduate Business Learning Center in Hartford, CT. Ram Gopal, department head of Operations and Information Management at UConn, gave welcoming remarks highlighting UConn’s new MS in Business Analytics and Project Management program that is now available at the Hartford campus. The first presenter, Pete Bothwell, Senior VP of Enterprise BI & Analytics at Travelers, focused on analytics in the property and casualty environment. The second presenter, Jon Sall, co-founder and Executive Vice President of SAS, demonstrated the use of JMP, a SAS tool used for graphic data analysis which can be used to bundle large amounts of data into meaningful statistical graphics. He used it to showcase processing times for data sets of various sizes and shapes, ending with an impressive graphical display of census data over time cycling through thousands of variables. Finally, the last presentation delivered by Radhika Kulharni, VP R&D Analytics at SAS, complemented John Sall’s topic on how SAS can be used to process large amounts of data in seconds. She focused on the use of distributed computing environments such as SAS GRID and products such as SAS Scoring Accelerator and SAS Analytics Accelerator which are used to process data inside the database itself, minimizing I/O and processing time. She then discussed the use of applying these analytic capabilites to customer behavior: for example, tailoring a coupon for a particular customer.

To view more on SAS Visual Analytics tool:
http://www.sas.com/technologies/bi/visual-analytics.html

For more about JMP:
www.jmp.com