Best Coding Practices for a Rigorous Statistical Workflow

This seminar presents strategies for writing clean, tidy, beautiful code that supports Rigor, Reproducibility, and Transparency (RRT) in data management and analysis for scientific research projects. Have you ever had to work with code from a colleague where you lost the trail of how data were recoded or why? Have you ever had trouble finding the latest version of stats output that went into the paper you submitted? Drawing on years of collaborative experience, the presentation will cover practical tips and techniques including version control, documenting workflows, and writing clean, readable code (with specific examples of “Do this” “Not that”) that facilitates collaboration and long-term project maintenance for your future-self in addition to collaborators or the scientific community. Attendees will leave with specific tips of how to structure their code and keep it clean to support high-quality, reproducible research.

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