Orange County and Inland Empire SAS Users Group/2013

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The mission of OCIE SUG is to help SAS users in Orange County, Riverside County, and San Bernardino County in Southern California to learn more about SAS and network with other SAS users. We are a resource for the SAS community all over Orange County and Inland Empire region of California.


8AM – 8:45 AM: Welcome and Introductions

Our leader, Lida Gharibvand, President of OCIESUG

8:45AM – 9:45AM: Together at Last: Spatial Analysis and SAS® Mapping

Presenter: Jeff Phillips via WebEx, SAS® Institute

  • Abstract: Spatial analysis and maps are a perfect match. Spatial analysis adds intelligence to your maps; maps provide context for your spatial analysis. The geostatistical tools in SAS/STAT® software can model and predict a variety of spatial data. SAS mapping tools enable you to create rich visualizations from that material. This presentation introduces a new framework that combines SAS spatial analytics with SAS mapping. Examples demonstrate how you can use the SAS/GRAPH ANNOTATE facility with the transparency specification (new in SAS 9.3) to combine a predicted spatial surface with traditional SAS/GRAPH maps, and show how to tap into the additional mapping resources of ESRI software through the SAS Bridge for ESRI. These tools empower you to make more intelligent maps and more informative spatial analyses.


9:45AM - 10AM: Morning break

10AM - 11AM: Tips and Strategies for Mixed Modeling with SAS/STAT® Procedures

Presenter: Jill Tao via WebEx, SAS® Institute

  • Abstract: Inherently, mixed modeling with SAS/STAT procedures, such as GLIMMIX, MIXED, and NLMIXED, is computationally intensive. Therefore, considerable memory and CPU time can be required. As a result, the default algorithms in these procedures might fail to converge for some data sets and models.

This paper provides recommendations for circumventing memory problems and reducing execution times for your mixed modeling analyses.

  • This paper also shows how the new HPMIXED procedure can be beneficial for certain situations, as with large sparse mixed models. Lastly, the discussion focuses on the best way to interpret and address common notes, warnings, and error messages that can occur with mixed models.

11AM - 12AM: Output Delivery System Tips and Techniques

Presenter: Kirk Paul Lafler, Senior Consultant and SAS Press speaker

  • Abstract: This presentation provides Output Delivery System (ODS) programming tips and techniques to help improve the way your SAS® data and output appears by turning tired-looking output containing lifeless monospace fonts into great looking information with a purpose. ODS introduces exciting new features for your output. Using built-in format engines, ODS provides SAS users with exciting capabilities to produce “quality” and publishable output. This presentation shows how to identify output objects, select the output of interest with selection lists, send selected output to open destinations including RTF, MS Excel spreadsheets, PDF, HTML, and SAS data sets.


12PM - 1PM: Lunch Break

1PM - 2PM: Processing Large Data in SAS® and using SAS/ACCESS


Presenter: Ron Coleman in person in Irvine, CA, SAS® Institute

  • Abstract: As data grows in volume, we find our jobs slowing down. What are we to do? This presentation looks at the SAS system and data set options, along with code techniques to speed up common joins as well as explore and compare the strengths and weaknesses of SQL and the DATA step to address different situations. The discussion will include how to work with large tables in both SAS and a DBMS, and strategies to use when joining tables in the two different systems.

2PM - 3PM: Review of Survival Analysis in SAS® 9.3


Presenters: Dr. Mark Ghamsary, PhD and Keiji Oda, Loma Linda University

  • Abstract: Survival analysis involves the modeling of time-to-event data whereby death or failure is considered an "event". The graphical presentation of survival analysis is a significant tool to facilitate a clear understanding of the underlying events. The analysis of survival data requires special techniques because the data are almost always incomplete. Investigators follow subjects until they reach a pre-specified endpoint (for example, death). However, subjects sometimes withdraw from a study, or the study is completed before the endpoint is reached. We will review the capabilities of SAS 9.3 to analyze survival data.


3PM – 3:15PM: Afternoon break

3:15PM – 4:15PM: PROC SQL from the SAS ® Programmer›s Point of View

Presenter: Ron Coleman from Irvine, CA, SAS® Institute

  • Abstract: This presentation offers an introduction to SQL syntax from a SAS point of view. SELECT

statements are covered in-depth with explanations of the FROM, WHERE, ORDER BY and GROUP BY statements. Additional features like the CASE …END statement and the coalesce() function are included, as well as a consideration of table joins.

4:15PM - 5PM: Networking and Socializing