5  Resources

All lab members are invited to expand these lists. Please correct or report any broken links or other errors.

5.1 Programming

• How to use Git/Github with R blog post by David Keyes on Rfortherestofus.com
• Happy Git and Github for the useR a more extensive e-book
• “Putting the R into Reproducible Research” (2019) by Dr Anna Krystalli
• Project-oriented workflow (2017) by Jenny Bryan, 2017
• Markdown Cheatsheet by adam-p on github
• Good enough practices in scientific computing (2017) article from PLOS Computational Biology by Wilson et. al.

5.2 Writing

• Writing your first academic paper (2016) is a helpful guide by Jeff Leek, a biostatistician at Johns Hopkins.
• The 12 steps to writing a paper and staying sane (2014) from the Health Research Journey blog by Jodie Oliver-Baxter and Lynsey Brown

5.3 Methods

5.3.1 Cost-effectiveness/health technology assessment

• Cost-Effectiveness in Health and Medicine (2016) is considered ‘the Bible’ of CEA

5.3.2 Statistical methods

• Statistical Rethinking book, course, and exercises by Richard McElreath
• Value of Information Analysis in Models to Inform Health Policy, review paper by Christopher H. Jackson, Gianluca Baio, Anna Heath, Mark Strong, Nicky J. Welton, and Edward C.F. Wilson
• Visual explainer for multi-level modeling

5.3.3 Data science / Machine learning

• BIMS 8382 Intro to Biomedical Data Science is a course by Stephen Turner at the UVA School of Medicine with great lecture notes and R code

• Data Science from Stratch (Sean Kross) is a helpful list of resources

• Machine Learning Methods That Economists Should Know About (2019), review paper by Susan Athey and Guido W. Imbens

5.3.4 Other

• Decision Modeling (2022), a free PDF book by David M. Tulett, is a great resource on applying optimization and mathematical modeling to decision problems.