The Effective Statistician - in association with PSI
The FAIRification Of Research In Real-World Evidence: A Practical Introduction To Reproducible Analytic Workflows Using
Jun 10, 2024
Experienced researcher Janick Weberpals discusses reproducible analytic workflows, FAIR principles, and challenges in Real-World Evidence research. Integration of Git and R enhances transparency and collaboration. Insights on best practices, coding, and implementation steps for reliable findings.
31:58
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Quick takeaways
- Integrating tools like Git and R enhances transparency and collaboration in research.
- Adopting FAIR principles ensures findability and interoperability of code for efficient collaboration.
Deep dives
Importance of Reproducibility and Transparency in Statistical Programming
Ensuring reproducibility and transparency in statistical programming is crucial for the integrity and credibility of research. By using tools like Git for version control, researchers can create a detailed audit trail of code changes, allowing others to replicate analyses accurately. Providing access to code along with methodologies enables easier implementation of new techniques in research, fostering collaboration and validation.
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