Exploring Interference in Causal Inference

For my Causal Inference capstone class, my class partner Siddhant Singh and I worked to learn and create a tutorial for interference in causal inference, which occurs when the treatment of one subject “interferes” with the treatment of another, making it difficult to estimate average causal effects. Examples of when this happens include vaccination trials, where if a large portion of the population is vaccinated, herd immunitiy begins to provide protection, biasing traditional estimates of average causal effects. Our project can be found here.