S5E3: From Cashew Nuts to Counterfactuals

About this episode

The episode features a discussion on causal inference with Dr. Peter Tennant, focusing on observational studies and randomized trials.

In this episode of SERious Epidemiology, Matt and Hailey welcome guest Dr. Peter Tennant to discuss chapters 2 and 3 of Causal Inference: What If. After learning about Peter’s late ‑discovered love of cashew nuts despite past nut allergies, we shift to a discussion about observational studies and randomized trials. Like the textbook, we start talking about why randomized trials are a helpful framing tool to talk about the identifiability assumptions for causal inference. We then introduce concepts such as marginal and conditional effects, exchangeability, positivity, and consistency. We start to dive into the subtle distinctions in some of these concepts: confounding vs. lack of exchangeability due to random error, the underappreciated practical importance of positivity, and how consistency relates to well‑defined interventions.

People in this episode

Hosts: Matt, Hailey

Guest: Dr. Peter Tennant

Topics covered

• causal inference
• observational studies
• randomized trials
• marginal effects
• conditional effects
• confounding
• positivity

Keywords

• causal inference
• observational studies
• randomized trials
• marginal effects
• conditional effects
• confounding
• positivity
• exchangeability
• consistency

Mentioned in this episode

Books & works: Causal Inference: What If

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