Course Resources

Documentation, books, and references for Computational Foundations for Pharmacometrics in R.

Tip

How to use this page: This course is designed around practice. Use these resources when you want official documentation, deeper explanations, or examples beyond the course lessons.

Core R Resources

Tidyverse and Data Wrangling

Visualization

Modeling in R

These resources support the modeling lessons in this course and help connect basic R modeling to more advanced pharmacometric workflows.

Reproducible Workflows

Pharmacometrics-Oriented R Packages

These packages are used in more specialized pharmacometric workflows and appear in later AEAcademy PMx courses.

Core Books

Wickham H, Çetinkaya-Rundel M, Grolemund G. R for Data Science.
Wickham H. Advanced R.
Xie Y, Allaire JJ, Grolemund G. R Markdown: The Definitive Guide.
Xie Y, Dervieux C, Riederer E. R Markdown Cookbook.
Chang W. R Graphics Cookbook.

Concepts Worth Revisiting

Data frames and tibbles
Pipes and readable code
Structural data checks
Missing values and BLQ handling
Grouped summaries
Joins and dataset assembly
Individual profiles
Linear and log-scale visualization
Reproducible project organization

Suggested Reading Path

For beginners, start with R for Data Science and the tidyverse documentation.

For learners preparing for modeling workflows, focus on reproducible project structure, data QC, individual profile visualization, and the transition from exploratory analysis to model-ready datasets.