Event

Apply causal inference methods to real-world evidence and clinical research

This course introduces causal inference principles and methods to support decision-making using real-world evidence (RWE) and clinical trial data. It focuses on addressing bias, defining appropriate causal estimands, and applying causal methods and modeling in regulatory, payer, health technology assessment (HTA), and clinical guideline contexts.

Technical topics include:

• Causal principles, directed acyclic graphs (DAGs), and target trial emulation
• Common design biases, including time-zero bias and immortal time bias
• Methods for baseline confounding, including multivariable regression and propensity scores
• Methods for time-varying confounding, including the g-formula, marginal structural models with inverse probability of treatment weighting, and rank-preserving structural failure-time models with g-estimation
• Estimand selection for observational studies and clinical trials, including trials affected by treatment switching
• Applications of causal machine learning and causal artificial intelligence (AI)

This course includes tools and concepts that can be immediately applied, including:

• Frameworks for designing and analyzing observational studies and clinical trials
• Application of causal methods in HTA case examples, including single-arm trials with external control arms and trials affected by treatment switching
• Practical guidance on selecting appropriate estimands to directly address decision problems
• Recommendations for applying causal inference methods and estimands in causal modeling
• Insights into HTA agency perspectives, including acceptance of and barriers to causal inference approaches

Participants will gain the knowledge and skills to apply causal inference methods, estimands, and causal modeling approaches to generate robust, decision-relevant evidence across healthcare settings. The course is designed for stakeholders and researchers across all areas of health and healthcare.

PREREQUISITE: Basic knowledge in epidemiologic study designs, analytic methods and biases (including the concept of confounding) is helpful.

Register Here

*Conference attendance is not required to attend an ISPOR Short Course. Separate registration is required for conference attendees.

Visit the ISPOR Europe 2026 Program page to view all short courses offered.

Back to all short courses