Introductory Material on Some Causal Inference Topics

Leveraging Prognostic Baseline Variables to Gain Precision in Randomized Trials through Covariate Adjustment. [PDF]

The Assumptions a Causal DAG (directed acyclic graph) Encodes. [PPT] Note: contains animation, best viewed in slideshow mode.

Overview of Targeted Maximum Likelihood for Estimating the Causal Effects of a Single Time Point Treatment and of a Two Time Point Treatment. [PDF]

Johns Hopkins University

Measure-Theoretic Probability Theory 2014-2015

Asymptotic Statistics 2015

Essentials of Probability and Statistical Inference I: Probability. 2010-2013.

Essentials of Probability and Statistical Inference II: Statistical Inference. 2011-2013.

Adaptive Designs in Clinical Trials: 2009-2010.

Experimental and Non-experimental Designs for Estimating Causal Effects (140.665.01)-co-taught with Constantine Frangakis. Course created and implemented by Constantine. 2009-2014.

UC Berkeley

Statistics 131A: Statistical Inferences for Social and Life Scientists. Fall 2007.

Statistics 20: Introduction to Probability and Statistics. Spring 2007.