Course detail

Welcome to R-course for beginners

Program: EB (Epidemiology and Biostatistics)

This course introduces PhD students, clinicians, and researchers to coding in R with a focus on medical research and data. Participants will learn the essential skills needed to handle, clean, and analyze datasets typical of registry-based and clinical research. Participants will acquire the skills to import patient-level data, clean and structure data extracts, generate descriptive cohort summaries, and perform introductory time-to-event analyses such as Kaplan-Meier curves.

Over three days, participants will be guided through six modules of 3–4 hours each, combining short lectures with hands-on exercises and instructor support. The teaching follows the natural journey of a medical study: starting with raw medical data, moving through cleaning and preparation, and concluding with analyses and visualizations directly applicable to clinical research questions.

The course covers essential topics, including:

• Understanding R syntax and fundamental functions through medical examples (patients, diagnoses, treatments)
• Navigating RStudio efficiently for medical data analysis
• Importing and cleaning health datasets
• Data aggregation at patient and cohort level
• Creating figures and tables for publication (baseline table 1, Kaplan-Meier plots, etc.)
• Writing functions and simple algorithms
• Basics of survival analysis and time-to-event outcomes in R
• Structuring a reproducible medical research project in R (Scripts, documentation)
• Using R’s help features and effective Google search strategies
• And more

The first two days consist of in-class lectures and exercises, while the third day is dedicated to a coding lab, where participants integrate everything learned into a mini-project that mirrors real medical research.

 Who should attend

The course is designed for participants with no prior programming experience. Emphasis is placed on practical application, guiding students through the complete workflow from raw medical data to cleaned datasets and lastly to basic survival analyses. By the end of the course, participants will have a basic methodological foundation to apply R in registry-based studies, clinical trials, and other medical research contexts.   

Literature/Requirements

Installation of R and R-studio,

R: https://cran.rstudio.com/

R-studio: https://posit.co/downloads/

Prerequisites
None

Evaluation
Evaluation by written report. Passed/fail.

Important information concerning PhD courses: There is a no-show fee of DKK 3,000 for each course where the student does not show up. Cancellations are accepted no later than 2 weeks before the start of the course. Registered illness is of course an acceptable reason for not showing up on those days. Furthermore, all courses open for registration approximately four months before start of the course.

We cannot ensure any seats before the deadline for enrolment, all participants will be informed after the deadline, approximately 3 weeks before the start of the course.

To attend courses at the Doctoral School in Medicine, Biomedical Science and Technology you must be enrolled as a PhD student.

You may find more information in our FAQ: https://phd.moodle.aau.dk/local/page/faq 

For inquiries not described in the FAQ, please contact the PhD administration at phdcourses@adm.aau.dk. When contacting us please state the course title and course period. Thank you.