Past Presentations
April 9 , 2008
Diane Fairclough, DrPH
University of Coloarado Denver
Colorado Health Outcomes Program
"An Interactive Randomization Program"
Allen Malone
Kaiser Permanente
“A simple technique to hide passwords in program files and logs”
January 9 , 2008
Richard Allen
Peak Statistical Services
"Introduction to Using the Data Step Hash Object with Large Datasets"
Tim Barnes
Galileo and Travelport
"How SAS Macros Made My Life Easier!"
July 11, 2007
Nikki Carroll
Kaiser Permanente
"Tap Into the Power of Formats"
Brenda Beaty
UCHSC/COHO
April 11, 2007
Paul Hansen
Anthem
Using SAS to span multiple data warehouses to facilitate data access, analysis, and decision making across multiple regions in Health Care.
Using SAS for Data Warehousing
Katie Benton
Analysis System
George Hage
Associate Director of Statistical Programming
OSI Pharmaceuticals
"Get Control of Your Life(test)"
While the graphical representation of the output from the LIFETEST procedure is improving with higher versions of SAS and ODS, there is still not enough control for the Medical Writers, Clinicians, and Statisticians at OSI Pharmaceuticals. There has been code available for some time to export the LIFETEST data, both the Kaplan-Meyer estimates and the censored points, to a dataset so that they can be plotted with other procedures within SAS, e.g., GPLOT. Often, however, it is desired to control line colors and types; axis length, divisions, and labels, as well as titling, legends, etc. It is also often desirous to annotate the plots with various statistics, some out of LIFETEST and some out of other procedures. OSI Statistical Programming staff uses this procedure and subsequent graphs often, thus it was decided to macroize this process. This talk will cover the need, macro, options, and results of our MLIFETST macro.
Click links below to download materials:
Control Your Life(test).ppt
Shahar Boneh
Professor of Statistics at the Metropolitan State College of Denver:
Statistical Simulations Using SAS
I will show how I use SAS to simulate various statistical models, when I teach advanced topics in statistics. SAS programs are written by students based on model specifications. The models are then analyzed using the appropriate SAS procedures. Examples will include simulations of survival data, time series, and stochastic optimization.
Presentation.doc