Clinical Evidence Lab: Study Design & Advanced Methods
Design rigorous studies, reduce bias, and generate defensible evidence for real-world clinical decisions.
This advanced module deepens participants’ expertise in study design, causal inference, and advanced analytical strategies in clinical research. Building upon foundational knowledge, the course focuses on designing robust studies, minimizing bias, and generating reliable real-world evidence.
Participants critically evaluate research protocols, explore advanced epidemiological methods, and apply causal reasoning frameworks to clinical datasets. The goal is to enable professionals to independently design, assess, and optimize high-quality research projects.
As part of the modular certificate structure, this course can be taken individually or applied toward the Master's program “Clinical Research (M.Sc.)” at DIU.
Key facts
Degree
Participation without an exam:
Certificate of Enrollment
Participation with an exam:
ECTS CertificateCourse start
16 August 2026
Duration
5 months
Course location
Online
Course format
part-time
Credit points
10 ECTS
Language
English
Course fee
€3,445
Our course is designed for:
- Clinical research professionals who want to deepen their expertise in rigorous study design, causal inference, and advanced analytical strategies.
- Healthcare and life sciences specialists who contribute to research projects and want to assess protocols, bias, and real-world evidence more confidently.
- Professionals preparing for leadership roles in clinical research, regulatory affairs, epidemiology, or health data science.
Scientific Directors
Dr. Ben M. W. Illigens, MD, MBI
Instructor in Neurology, Beth Israel Deaconess Medical Center Boston, MA United States and Director, German Sites Development Principles and Practice of Clinical Research Harvard T.H. Chan School of Public Health
Managing Director, CEO, D4L data4life gGmbH
Prof. Dr. med. Timo Siepmann, FAHA, FESO
Senior Attending Physician (Deputy Chief Physician), Medical Faculty and University Hospital Carl Gustav Carus, TUD Dresden University of Technology, Site Director, Principles & Practice of Clinical Research (Harvard TH Chan School of Public Health)
Content & qualifications
This module deepens your expertise in study design, causal inference, and advanced analytical strategies in clinical research. You will learn how to design robust studies, minimize bias, and generate reliable evidence for real-world clinical decisions.
What you will cover
- Advanced study designs, including cohort and case-control studies
- Registry-based studies and real-world evidence frameworks
- Bias, confounding, and effect modification
- Causal inference in clinical research
- Advanced regression modeling
- Survival analysis basics
- Critical appraisal of study protocols
- Ethical and regulatory considerations in research design
What you will be able to do
After completion, you will be able to:
- Design robust clinical research studies
- Apply causal inference principles
- Identify and mitigate bias and confounding
- Evaluate complex research protocols
- Interpret advanced regression and survival analyses
- Critically assess real-world evidence studies
How you will learn
- Research-focused seminars
- Applied case studies
- Methodological workshops
- Critical appraisal exercises
- Interactive discussions with faculty experts
Admission requirements
- A suitable academic and/or professional background is recommended.
- In general, you can enroll in an individual course even if you do not meet the admission requirements for the full Master’s degree program.
When requesting participation, please briefly outline your educational pathway and professional background. Based on your profile, we will either invite you to a study advisory appointment or—if direct entry is possible—send you a module agreement for enrollment.
Personal advice
FAQs
Who is this module for?
This module is designed for clinical research professionals, healthcare and life sciences specialists, and anyone who wants to build practical skills in applied biostatistics, R/RStudio, and clinical data workflows—including EHR-based research.
Can I take this module without enrolling in a full Master’s program?
Yes. In general, you can enroll in this course without meeting the formal admission requirements for the full Master’s degree program. The module is individually bookable.
What will I learn in this module?
You’ll deepen your ability to design high-quality clinical studies, evaluate protocols, address bias and confounding, and apply advanced methods commonly used in real-world evidence and outcomes research.
Do I need to complete other modules first?
Prior foundational knowledge in clinical research methods is recommended. If you’re unsure whether your background is a fit, send us your profile—our Study Advisory Team will advise you on the best entry point. Get in contact with Study Advisory.
Are there admission requirements?
A suitable academic and/or professional background is recommended. When requesting participation, please briefly describe your educational pathway and professional background. Depending on your profile, we will either invite you to a study advisory appointment or—if direct entry is possible—send you a module agreement for enrollment. Request course registration now.
What learning format can I expect?
Expect a practice-oriented format with guided exercises, real-world datasets, hands-on workshops in R/RStudio, and structured self-study—focused on skills you can apply immediately in clinical research settings.
What do I receive after completion?
After successful completion, you receive an official DIU certificate of completion.
How do I request participation?
Email us with a short description of your educational pathway and professional background, plus your preferred contact method (email or phone). Our Study Advisory Team will follow up with next steps and participation options. Request course registration now.
