Statistics & Data Science · Causal Inference
A topic within Causal Inference, itself one of 10 topics in that field and part of Statistics & Data Science.
No prior grounding assumed.
The C-Word: Scientific Euphemisms Do Not Improve Causal Inference From Observational Data
Miguel A. Hernán · 2018
Argues that hedging a causal question behind associational language does not make the analysis more rigorous, it just hides the causal assumptions…
Assumes you know the vocabulary.
Causal Inference: What If
Miguel A. Hernán & James M. Robins · 2020
Rebuilds the whole causal-inference toolkit — potential outcomes, identifiability conditions, g-methods for time-varying treatment — around a single…
+1 more at this level
3 works
Miguel A. Hernán
Argues that hedging a causal question behind associational language does not make the analysis more rigorous, it just hides the causal assumptions being made from the scrutiny they need.
link checked 17 Sept 2026Miguel A. Hernán & James M. Robins
Rebuilds the whole causal-inference toolkit — potential outcomes, identifiability conditions, g-methods for time-varying treatment — around a single running question: what randomised trial would this observational analysis have to emulate to be believed.
link checked 17 Sept 2026Esther Duflo and Sara Fisher Ellison (MIT OpenCourseWare)
Teaches the statistics social science actually relies on, with identification and what a coefficient can honestly be said to mean treated as the central problem rather than an afterthought.
link checked 17 Sept 2026