Learning resources

Courses, books and references for R, epidemiology and statistics

If you only pick one: Start with DDEA Introductory Course if you are completely new to R, or The Epidemiologist R Handbook if you know a bit of R and want to go straight to health science applications.

Getting started - learn R

Resource	What it is
⭐ DDEA Introductory Course	Introductory R course from the Danish Diabetes and Endocrine Academy - held once a year, materials freely available. Best starting point if you are completely new.
⭐ R for Data Science	Free e-book by Hadley Wickham - the standard reference for modern R with tidyverse. Concept-based, read from start to finish.
Cookbook for R	Task-based reference: “how do I do X?” with direct code examples. Strongest for its ggplot2 graphics recipes (legends, faceting, colours). Note: parts of the base-R and data-handling sections predate the tidyverse, so the syntax can differ from the rest of this guide.
Quick-R	Compact reference page for R syntax and statistics. Good for quick lookups mid-script.

Health science and epidemiology

Resource	What it is
⭐ The Epidemiologist R Handbook	Practical reference written for epidemiologists and health researchers - covers data cleaning, analyses and visualisation with health science examples. Most relevant chapters for register work: dates, joins, data cleaning, regression and survival analysis. Most pages in this guide link to the matching chapter.
⭐ Zheers R Coding Café	Notes and examples specifically for register data - local to Steno Diabetes Center Aarhus.
CRAN Task View: Epidemiology	Package list for epidemiology - incidence rates, matching, cohort analysis. Good starting point when looking for the right package.
CRAN Task View: Survival Analysis	Package list for survival analysis - Cox regression, Kaplan–Meier and competing risks.

Stuck? Look up common problems in Common errors, and learn how to ask a good question in Getting help (both in The Epidemiologist R Handbook). On DST you cannot share your confidential data when asking for help - simulate a small, fake dataset that reproduces the problem instead. Minimal Reproducible Example (Zheer’s R Coding Café) shows how.

Podcasts:

Resource	What it is
🎧 SERious Epi	Podcast on epidemiological methods in practice - study design, bias and analytical choices, discussed by experienced epidemiologists.
🎧 Causal Inference	Podcast on causal inference - methods, confounding and causal questions, in an informal conversational format.

Methods and statistics

Resource	What it is
Learning Statistics with R	Free e-book by Danielle Navarro - covers statistical theory and R implementation side by side, from basic probability to regression and ANOVA. Written for a non-mathematical audience. Relevant if you want to understand the statistics you are running, not just copy the code.
Causal Inference: What If (Hernán & Robins)	Free PDF - the standard reference on causal inference, confounding and DAGs. Epidemiological methods, not R.