CDISC with R
Build SDTM and ADaM datasets from raw trial exports, 30 hands-on sessions
About this course
CDISC with R is a self-paced online course teaching clinical data standards through a simulated Phase III trial (GLPX-1). It takes learners through a full pipeline: raw data through SDTM domains, ADaM datasets, to submission-ready outputs, working against deliberately flawed raw data, duplicate records, missing dates, conflicting values, to practise realistic problem-solving alongside standards compliance.
Learning objectives
- Build SDTM domains from raw clinical trial data
- Construct ADaM analysis datasets from SDTM
- Produce submission-ready outputs (including Define-XML and Dataset-JSON)
- Trace implementation decisions to specific Implementation Guide sections
- Handle realistic data problems: duplicates, missing dates, conflicting values
Who it is for
Statistical programmers, biostatisticians and R users entering clinical trial work. No prior CDISC knowledge is assumed.
Curriculum
- Setup
- SDTM foundations
- SDTM implementation
- ADaM datasets
- Submission outputs
11 exercises, each with executed code and computed answers. Targets SDTMIG v3.4, ADaMIG v1.3, Define-XML v2.1 and Dataset-JSON v1.1.
Format & materials
The public repository holds course sessions, exercises and build artifacts, maintained as an open book with continuous corrections. A private, paid-tier repository holds worked solutions and instructor materials.
Course site: https://sufyansuleman.github.io/cdisc-with-r/
Run this course for your group
I teach CDISC with R on demand for research groups, departments and companies, on site or online, adapted to your data and level.