The Effective Statistician - in association with PSI

R-packages - best practices and useful tools

Mar 24, 2025

Daniel Sabanés Bové, a statistician from Roche and Google and founder of Arconis consulting, discusses the transformative power of creating R packages for code reuse and collaboration. He shares insights on overcoming common coding challenges and emphasizes that starting to write packages might happen sooner than you think. With tools like usethis and testthat, Sabanés walks through his process from idea to launch. He also highlights the vibrant R community, filled with creativity, collaboration, and fun elements like hex stickers.

20:55

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Episode guests

Daniel Sabanés Bové

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Episode notes

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Quick takeaways

Creating R packages enhances code reuse and collaboration, addressing common challenges like documentation and readability to improve overall code quality.

A systematic approach to package development, starting with careful planning and prototyping, ensures effective organization and ongoing functionality as projects evolve.

Deep dives

The Importance of Creating R Packages

Creating R packages is essential for reusing code effectively and improving code reliability. One significant challenge in code reuse is the lack of documentation, which makes it difficult to understand the purpose and function of the code later on. Additionally, inconsistent coding styles and the use of vague variable names can further hinder code readability and maintenance. By encapsulating frequently used functions into packages, statisticians can not only enhance code organization but also streamline collaboration within teams.

Intro

2min

Journey into R Packages and Statistical Engineering

2min

Creating R Packages for Code Reusability

8min

Understanding Testing Frameworks for R Packages

2min

Unlocking R Packages: Community and Collaboration

8min

Interview with Daniel Sabanés Bové

What You’ll Learn in This Episode

✔ Why creating R packages is a game-changer for code reuse and collaboration.

✔ The most common challenges we face when reusing code—and how packages help solve them.

✔ When it actually makes sense to start writing a package (spoiler: earlier than you think).

✔ Useful tools like usethis, testthat, and RStudio features that simplify the process.

✔ Daniel’s step-by-step approach—from sketching ideas on paper to launching the finished package.

✔ How to write meaningful tests to keep your code working as your project evolves.

✔ Where and how to share your package with others—GitHub, social media, conferences, and even journals.

✔ The fun side of the R community: hex stickers, open-source collaboration, and more.

✔ How Daniel’s team at Arconis can help if you want expert support with your package development.

Why You Should Listen

If you work in biostatistics, health economics, or market access, this episode is packed with practical insights to help you collaborate more effectively. Whether you're a statistician looking to better support HTA submissions or a market access professional trying to understand statistical challenges, you’ll walk away with actionable strategies that can make a real difference.

Resources & Links

Resources & Links:
🔗 Arconis
🔗 Open Stats Working Group
🔗 Open Stats Guide
🔗 R Journal
🔗 Journal of Statistical Software
📌 R packages: usethis, testthat, and others
📌 Upcoming workshops on software engineering for R (Basel, Paris, Tokyo)
🔗 The Effective Statistician Academy – I offer free and premium resources to help you become a more effective statistician.
🔗 Medical Data Leaders Community – Join my network of statisticians and data leaders to enhance your influencing skills.
🔗 My New Book: How to Be an Effective Statistician - Volume 1 – It’s packed with insights to help statisticians, data scientists, and quantitative professionals excel as leaders, collaborators, and change-makers in healthcare and medicine.
🔗 PSI (Statistical Community in Healthcare) – Access webinars, training, and networking opportunities.

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