Transparency & Reproducibility Methods for Social Science Research
June 10-12, 2015
University of California, Berkeley
Research norms are changing faster than ever before. Repeated cases of scientific dishonesty, mistakes in data analysis, irreproducible findings, and publication bias in the literature, have prompted an impressive number of methodological, statistical, and technological innovations. There is a growing quantity of services and resources to archive and share data, report methods used to generate results, pre-register study plans, enable reproducibility of findings, as well as software tools to support transparent and collaborative workflows.
Sponsored by the Berkeley Initiative for Transparency in the Social Sciences, this workshop will provide participants with an overview of cutting-edge mechanisms for open and rigorous social science. The curriculum has been revamped and condensed compared to the 2014 edition, with sharper and more intense sessions, taught by academic leaders in the transparency movement. There will also be more space for collaborative work and hands-on skill building.
Students can expect to finish the program with a thorough overview and understanding of best practices for open, reproducible research, allowing them to remain in the vanguard of new scientific frontiers. They are encouraged to bring existing research questions and ideas based on their own interests, and seek support and feedback from instructors and other attendees.
This workshop is generously supported by the Alfred P. Sloan Foundation, the Laura and John Arnold Foundation, and the Center for Open Science.
Katherine Casey (Stanford University), Garret Christensen (UC Berkeley), Clara Cohen (UC Berkeley), Scott Desposato (UC San Diego), Eric Eich (University of British Columbia), Solomon Hsiang (UC Berkeley), Nicole Janz (University of Cambridge), Edward Miguel (UC Berkeley), Leif Nelson (UC Berkeley), Maya Petersen (UC Berkeley).
- Emerging Issues in the Practice of Empirical Social Science
- Ethics in Experimental Research
- False-positives, P-hacking, P-curve, Power Analysis
- Data Management & Statistical Analysis in R
- Pre-registration: Lessons from Medical Trials & Biostatistics
- Theory and Implementation of Pre-analysis Plans
- Disclosure & Reporting Standards
- Registration & Data-sharing through OSF and Dataverse
- Approaches to the Replication of Research
- Meta-analyses: New Tools & Techniques
- Next Steps in Changing Scientific Research Practices
The workshop is designed for researchers across the social science spectrum, from economics to political science, psychology, and other related disciplines. Ideal candidates include: (i) graduate or post-graduate students contemplating a research career, (ii) junior faculty eager to learn about new tools and techniques, (iii) staff from research organizations interested in using these methods, and (iv) journal editors or research funders curious about the implications for their work. Diversity in terms of background and academic discipline is encouraged.
Please contact Alex Wais (awais [at] berkeley [dot] edu) with any questions.