Eric Daza | Important Ideas in Causal Inference

Eric Daza | Important Ideas in Causal Inference

YouTube: https://youtu.be/K5nsSMJVIT0

Andrew Gelman and Aki Vehtari wrote a paper titled, "What are the most important statistical ideas of the past 50 years?". The first idea in the list is "counterfactual causal inference". Eric Daza (Evidation Health) walks us through the main ideas of the Gelman & Vehtari paper, drawing examples from several fields, including medical & healthcare statistics. 

Topics 0:00 - Coming up...Correlation vs Causation 1:20 - Most important statistical ideas over the last 50 years 6:10 - Counterfactual Causal Inference 9:40 - Assumptions Change between Applied Domains 21:10 - Propensity Score Methods 25:15 - Transportability of Scientific Results  26:30 - People don't want generalizable results 32:00 - Generic Computation Algorithms 37:00 - Reweighting 43:57 - Matching Methods 58:20 - Medical Data is Higher Dimensional that we think. 1:00:15 - Is a Trial Population Representative?  1:10:35 - Causal Models in the Future 1:18:45 - Apostates Welcome 1:21:45 - Scientific Debate