Course

Tools for Reproducible Real-World Analyses

Upcoming sessions:

University of York May 28, 2022

Past sessions:

Virtual May 24-25, 2021

Copenhagen Nov 2, 2019

New Orleans May 18, 2018

Barcelona Nov 7, 2018

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.

We 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 exercises reinforce the concepts and tools introduced. RStudio Cloud is used for exercises. Participants who wish to gain hands-on experience should bring their laptops.

Concepts

  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

Materials and Exercises

Slides, code, exercises, and other fun [PASSWORD PROTECTED]

Dataset and data dictionary for exercises [PASSWORD PROTECTED]

Supplemental Resources

coding style & culture

learning R

reproducible research