Course

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Tools for Reproducible Real-World Analyses

Short-Course Instructors: Carrie Bennette, Joshua Kraut, and Blythe Adamson

This course focuses on the concepts and tools of reproducible research and reporting of modern data analyses. The need for more reproducible tools in health economics and outcomes research is growing rapidly as analyses of real world data become more frequent, involve larger datasets, and employ more complex computations. This course will cover the principles of structuring and organizing a modern data analysis, literate statistical analysis tools, formal version control, software testing and debugging, and developing reproducible reports. Numerous real-world examples and an interactive class exercise will be used to reinforce the concepts and tools introduced. This course will use RStudio Cloud for exercises. Participants who wish to gain hands-on experience should bring their laptops.

Agenda

  1. What is reproducible research?
  2. Why is reproducibility so important?
  3. How do we get there?
    • Organizing data
    • Writing clear code
    • Disseminating code & findings
    • Catching mistakes

Course Materials and Exercises

Click here for slides, code, in-class exercises, and more fun things. 

Resources

coding style & culture

learning R

reproducible research