Non-SOT Event: Code Rigor and Reproducibility with R Boot Camp

This two-day intensive boot camp presented by the Columbia University Mailman School of Public Health fills a critical gap—many health researchers are using open-source code for substantial and complex data analysis projects, yet their training in coding did not cover techniques for efficient, rigorous, and reproducible code when scaling to large and complex projects. Led by an expert in open-source programming for environmental health research, this workshop will cover techniques that you can use to make R code more rigorous and reproducible for research projects. The workshop will alternate between seminar lectures and applied computational work, with approximately equal amounts of lecture and hands-on work over the course of the workshop. In addition, participants will have the option to apply the principles from day 1 of the workshop to an example of their own research code as an optional homework, with time reserved in day 2 of the workshop for one-on-one evaluations of their progress on making their own code more rigorous and reproducible.

Investigators at all career stages are welcome to attend, but to get the most out of this workshop, you should have experience in R programming and be actively using R for research. As part of the workshop we will ask you to bring and work on your own research code.

Capacity is limited. Paid registration is required to attend.