May 11-15, 2020 University of North Carolina at Chapel Hill Consortium for Statistical Development and Consultation in Social Intervention Research UNC School of Social Work
Mark Fraser and Din Chen will be presenting a topic on Bayesian intervention research, which they presented at last week’s SSWR with a lot of interest. **Please RSVP to Brenda Vawter by Tuesday, January 24th, if you plan to attend … Read more
Researchers recommend tools that can maintain and improve quality in assisted living communities August 3, 2016 By Susan White Researchers from the University of North Carolina’s Cecil G. Sheps Center for Health Services Research and the UNC School of Social … Read more
He, H., Wu, P. & Chen, D. (Eds.). (2016). Statistical Causal Inferences and their Applications in Public Health Records. Springer. http://www.springer.com/us/book/9783319412573
Gary L. Bowen, Todd M. Jensen & James A. Martin (2016) A Measure of Comprehensive Airman Fitness: Construct Validation and Invariance Across Air Force Service Components, Military Behavioral Health, 4:2, 149-158, DOI: 10.1080/21635781.2015.1133345 http://dx.doi.org/10.1080/21635781.2015.1133345
Instructor: Kirsten Kainz, Ph.D.
The workshop will include lecture and statistical analysis components. By the end of the workshop participants will be able to critically evaluate research that uses propensity score analysis so as to provide expert peer reviews and conduct defensible propensity score analyses using recommended practices.
Instructors: Matthew Howard, Ph.D. and Ding-Geng (Din) Chen, Ph.D.
This two-day workshop tutorial provides a most up-to-date development and a thorough presentation on systematic review and meta-analysis models with detailed step-by-step illustrations and implementation using R/Stata.
Instructor: Roderick Rose, Ph.D.
Participants will be conversant in the frameworks and will understand the strengths and weaknesses of each method, and obtain limited hands-on experience with each. Participants will be able to apply this knowledge in a practical sense in research and evaluation design, analysis, grant writing, and reviews.
