Where: American Statistical Association (ASA) Biopharmaceutical Section (BIOP), European Federation of Statisticians in the Pharmaceutical Industry (EFSPI)
Who: Currently more than 40 statisticians from more than 30 organizations
What: Engineer packages and promote best practices
What you will learn here
Understand the basic structure of an R package
Create your own R
Learn about & apply professional development workflow
Learn & apply fundamentals of quality control for R
Get crash-course in version control and modern collaboration techniques on GitHub.com
Learn how to make an R available to others
Do we still need to learn this - AI can do it?
In the past, carpenters exclusively used saw, hand drill, and hammer
For a long time now, we have power tools, like electric saws and drills
And we have had computer aided design (CAD) software for decades
We have even 3D printers, which can produce furniture directly
Nevertheless, carpenters still start their apprenticeship by learning how to use a saw and hammer, and build furniture by hand
In the same way, we still need to learn the basics of good software engineering, even though AI tools can help us later to execute the work faster and more efficiently
What do we mean by GSWEP4R*?
Applying concept of “Good XYZ Practice” to SWE with R
Improve quality and longevity of R code/packages
Not a universal standard; we share our perspectives
Collection of best practices
Do not reinvent the wheel: learn from the community
Why care about GSWEP4R?
R is one of the most successful statistical programming languages
R is a powerful yet complex ecosystem
Core component: R packages
Mature user & contributor community
Where deeper understanding is crucial, even to just assess quality
Important: to use this work you must provide the name of the creators (initial authors), a link to the material, a link to the license, and indicate if changes were made.
