Methods for Reproducible Population Health and Clinical Research is focused on key principles of rigorous and reproducible population health and clinical research. The course provides introductory technical training in collaborative workflows and reproducible programming practices using GitHub and R as well as core topics related to research integrity and scholarly publishing, including academic incentives, authorship, code and data sharing requirements, preregistration, conflicts of interest, and reporting guidelines. Content is designed for health policy, biomedical data science, epidemiology, and computer science graduate students supported by NIH training grants with reproducibility training requirements. Students in such programs should consult with their program director to ensure that this course will fulfill specific requirements of their program. Prerequisite: Basic knowledge of R.
2 units · Medical Option (Med-Ltr-CR/NC)
Methods for Reproducible Population Health and Clinical Research is focused on key principles of rigorous and reproducible population health and clinical research. The course provides introductory technical training in collaborative workflows and reproducible programming practices using GitHub and R as well as core topics related to research integrity and scholarly publishing, including academic incentives, authorship, code and data sharing requirements, preregistration, conflicts of interest, and reporting guidelines. Content is designed for health policy, biomedical data science, epidemiology, and computer science graduate students supported by NIH training grants with reproducibility training requirements. Students in such programs should consult with their program director to ensure that this course will fulfill specific requirements of their program. Prerequisite: Basic knowledge of R.
Offered in Spring 2026 at Stanford University.