Eric Daza | Important Ideas in Causal Inference Data & Science with Glen Wright Colopy

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. 
Topics0:00 - Coming up...Correlation vs Causation1:20 - Most important statistical ideas over the last 50 years6:10 - Counterfactual Causal Inference9:40 - Assumptions Change between Applied Domains21:10 - Propensity Score Methods25:15 - Transportability of Scientific Results 26:30 - People don't want generalizable results32:00 - Generic Computation Algorithms37:00 - Reweighting43:57 - Matching Methods58:20 - Medical Data is Higher Dimensional that we think.1:00:15 - Is a Trial Population Representative? 1:10:35 - Causal Models in the Future1:18:45 - Apostates Welcome1:21:45 - Scientific Debate