Causal Effects - Introduction to the Potential Outcomes Framework

Explore the fundamentals of causal effects in this introductory video from a series on the topic. Delve into the Potential Outcomes Framework and learn about three distinct types of causal effects. Discover how to formulate these effects and gain insights into their applications in observational data analysis. Cover key concepts including the three types of variables, Individual Treatment Effect (ITE), Average Treatment Effect (ATE), and Average Treatment Effect of Treated/Controls (ATT/ATC). Examine practical questions and real-world applications of these concepts. Prepare for future videos in the series that will expand on computing causal effects from observational data. Access additional resources and readings to deepen your understanding of causal inference methods and principles in social research.

Introduction -
Causal Effects -
3 Types of Variables -
Potential Outcomes Framework -
3 Types of Causal Effects -
1 Individual Treatment Effect ITE -
2 Average Treatment Effect ATE -
2.1 ATE in RCTs -
3 Average Treatment Effect of Treated/Controls ATT/ATC -
Practical Questions -