The Causal Inference and Adaptive Trial Design Workshop occurred on Wednesday, May 10, 2017, in Washington DC.
Instructors:
Mark van der Laan, PhD
Professor, Biostatistics and Statistics
University of California, Berkeley School of Public Health
Maya Petersen, MD, PhD
Associate Professor, Biostatistics and Epidemiology
University of California, Berkeley School of Public Health
Yeh-Fong Chen, PhD
Mathematical Statistician
U.S. Food and Drug Administration
Materials:
Presentations:
SESSION 1: CAUSAL INFERENCE
- Part I: From causal questions to the statistical estimation problem: Introduction using single time point interventions
Maya Petersen, University of California, Berkeley
Slides - Part II: Statistical estimation and interpretation: Introduction using single time point interventions
Mark van der Laan, University of California, Berkeley
Slides 1
Slides 2 - Part III: From causal questions to the statistical estimation problem: Extension to multiple/longitudinal interventions
Maya Petersen, University of California, Berkeley
Slides - Part IV: Statistical estimation and interpretation: Extension to multiple/longitudinal interventions
Mark van der Laan, University of California, Berkeley
Slides
SESSION 2: ADAPTIVE DESIGN
- Part V: Targeted group sequential adaptive designs for learning the optimal individualized treatment rule
Mark van der Laan, University of California, Berkeley
Slides - Part VI: Utilizing seamless adaptive designs and considering multiplicity adjustment for NASH clinical trials
Yeh-Fong Chen, U.S. Food and Drug Administration
Slides