Causal analysis essentials

Module 4

Outline

• Recall the essential features of experimental study designs
  • Learning the vocabulary of causal analysis
• Get a visual intuition of causal pathways, including challenging elements:
  • Collider variables
  • Confounder variables
  • Mediator variables
• Discuss the correct causal model to capture the association among exposure, outcome and other covariates, (including challenging ones)
• Define causal outcomes and choosing the appropriate “estimands”:
  • ATE, ATT, or ATU?
• Devise statistical methods to estimate ATE, ATT, and ATU based on research question and (sub)population of interest

Lecture slides

View lecture slides in full screen  

Practice slides

View practice slides in full screen  

Practice input data (as subfolder)

Practice R code (as .R file)