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

 

 

Rss Apple Podcaster
Podden och tillhörande omslagsbild på den här sidan tillhör Glen Wright Colopy. Innehållet i podden är skapat av Glen Wright Colopy och inte av, eller tillsammans med, Poddtoppen.

Data & Science with Glen Wright Colopy

Eric Daza | Important Ideas in Causal Inference

00:00