Research Design and Analysis Core
The Research Design and Analysis Core provides all Pepper Center investigators statistical support from the beginning to end of all research projects. By serving as a central hub of statistical expertise, the Core ensures smooth delivery of statistical knowledge and rigor across the spectrum of scientific research at the Center. In addition, the Core guides all trainees through each step of the process, ensures the quality of Center research studies, and ultimately enhances research on predictors, characteristics, and outcomes of late-life disability, especially in vulnerable populations.
John Boscardin, PhD
Professor, Division of Geriatrics
RDAC Development Project Highlight:
As a project highlight, Dr. Boscardin has developed a SAS macros to determine optimism for logistic and Cox regression model selection and fitting for selection methods including the novel Best AIC/Best BIC subset selection methods .
The work was presented at the Global and Regional SAS conferences in 2015 and has resulted in numerous requests from researchers around the world for use of the software. In addition, based on users’ feedback, the RDAC is revising the macros for re-release.
Specific proceedings papers resulting from this SAS macros include:
- Estimating Harrell's Optimism on Predictive Indices Using Bootstrap Samples (Yinghui Miao, Irena Cenzer, Katharine Kirby, John Boscardin). SAS Global Forum Proceedings, 2013.
- Optimism of Best Subset Selection by AIC/BIC for Prognostic Model Building (Yinghui Miao, Irena Cenzer, Katharine Kirby, John Boscardin). Western SAS Users Proceedings, 2013
If you are interested in receiving the macros, please email Dr. Boscardin.