BITSS: Research Transparency

Instructor(s):

There is growing interest in research transparency and reproducibility across the social sciences. This workshop is a crash course on the problems of publication bias, inability to replicate research, and specification searching (or p-hacking, among other names) that have heretofore caused researchers problems. We will cover recent methodological progress in this area, including study registration, pre-analysis plans, disclosure standards, and open sharing of data and materials, drawing on experiences in economics, political science, and psychology, as well as other social sciences. We also engage hands-on with workflow-related software developments that help a researcher make their work more reproducible, particularly version control and dynamic documents, which can accurately track all changes made to code and make one's entire analysis reproducible with a single click.

Day 1
  • Introduction to Research Transparency
  • The Problems: Publication Bias, Specification Searching/P-Hacking
  • Preregistration and Pre-Analysis Plans
  • Data Sharing and Replication
Day 2
  • Reproducible Workflow
  • Organizing your work with the Open Science Framework
  • Version control with Git & GitHub
  • Dynamic Documents in Stata, R, and LaTeX

Application: Participants will be chosen through a competitive selection process. To apply, click on the "Registration" tab at the top of this page, provide your information, and select the course. Applicants must upload the following documentation:

  • Curriculum vita or resume;
  • Cover letter outlining your interest in the workshop, how you heard about it, and what you hope to get out of the program;
  • A letter of reference (optional).

Deadline Extended: The deadline for submitting applications has been extended to May 15, 2016. Accepted participants will be notified within approximately two weeks.

Fee: There are no tuition fees for this workshop.

Tags: reproducibility, data management, transparency

Course Sections