Learn how to master SDTM domains with our in-depth guide
Whether you’re new to SDTM, or need a refresher, this guide provides a thorough reference for those looking to accurately implement SDTM domains.
Why this guide is a must-have:
📌 Gain a clear breakdown of SDTM domains, and how each domain fits into your clinical submission package
💡 A key step in understanding SDTM core variables and roles
⚠️ Teaches you how to avoid common implementation errors, with best practices for mapping variables into domains
The top 3 critical failures around SDTM domain implementation include:
- Misunderstanding domain purposes (which can lead to misaligned or inconsistent datasets & validation errors)
- Incorrect categorization of observations – which causes structural issues in SDTM datasets
- Improper use of SDTM variables and roles. This lack of knowledge can result in data submission delays or rejection
What you’ll learn in this guide:
Gain practical insights, not just theory. Specifically you will learn:
- A breakdown of SDTM domains:
- What each domain is
- The role of the domain (so you don’t misclassify data)
- How to apply the domain in datasets
- How general observation classes differ from other classes, such as special purpose domains, and how they’re used
- SDTM variable roles and related categories
- Best practices for correctly mapping variables to domains
Submit the form now to download this free resource➡️
关于作者
Subject Matter Expert & Solutions Consultant
Ed Chappell, Solutions Consultant with over 15 years’ tenure, is a recognized expert in clinical data programming and SDTM dataset mapping. He has been instrumental in developing the dataset mapper, delivering advanced training on SEND and SDTM standards, and supporting customers with FDA submissions and Interim Analysis SDTM needs.
