The ASA Oklahoma Chapter is happy to be hosting the 2017 ASA Traveling course entitled
“Quantile Regression in Practice”
Please use the links below to download addtional material for the workshop: (Use Right click + Save link as option to save the sas files below)
- Mortality data analysis for quantile-regression model selection
- Product rating analysis for product features effect and quantile-process-regression model selection
- Sales data analysis on advertising cost for single quantile-level regression
- Sales data analysis on advertising cost for quantile process regression
- Spatial data analysis using quantile regression
- When: March 31, 2017 11am-4pm (12:30-1:30 lunch included in registration)
Where: The University of Oklahoma Health Sciences Campus
College of Health Building (First Floor Auditorium)
801 NE 13th Street
Oklahoma City, OK 73104
Instructor: This half-day course will be presented by Dr. Yonggang Yao, principle research statistician developer at SAS®. His research interests are in applications on quantile regression, robust regression, and statistical learning. He has developed two SAS procedures, PROC QUANTSELECT and PROC HPQUANTSELECT and is also the key supporting developer for two other SAS procedures, PROC QUANTREG for quantile regression and PROC ROBUSTREG for robust regression.
Topic: Quantile regression is a modern statistical methodology for modeling quantiles, such as the median and the 5th and 95th percentiles. Accordingly, you can use quantile regression to study covariate-adjusted high or low-end responses without making assumptions about distribution profiles. Quantile regression is particularly useful when your data are heterogeneous, or when you cannot assume a parametric distribution for the response. Common application areas for quantile regression include market analysis, economics, environmental studies, and health science.
This tutorial provides an overview quantile regression methodology, with carefully chosen examples from a variety of fields, including treatment effect analysis, uncertainty measurement, value-at-risk analysis, and extreme value analysis. The presentation is appropriate for data analysts and statisticians who are interested in more flexible methods for heterogeneous data analysis. Familiarity with linear regression, histograms, and basic distribution functions is assumed.
Registration: Early online registration (https://www.123signup.com/event?id=nphjq) will run through March 27, 2017 with registration fees as follows:
Student Chapter Member $10.00
Student Nonmember/Retiree $25.00
Regular Chapter Member $50.00
Regular Nonmember $60.00
Late registration (after March 27) and onsite registration will be available for an additional $5 charge for member registrations and $10 nonmember registration.
Please see https://www.123signup.com/event?id=nphjq for more information on this course.
ASA Oklahoma Chapter Officers
The American Statistical Association (www.amstat.org)
The University of Oklahoma Health Sciences Center Department of Biostatistics and Epidemiology (www.publichealth.ouhsc.edu)
The Oklahoma Shared Clinical and Translational Resources (www.osctr.ouhsc.edu)
The Biomedical and Behavioral Methodology Core (www.ouhsc.edu/bbmc)