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
S00 Ep04 Pt 2 with Allison Meisner: Technical Deep-dive Into Optimizing Bespoke Clinical Models
S00 Ep04 Pt 1 with Allison Meisner: Winning the ASA Student Paper Competition and Research Overview
S00 Ep03 Pt03 with Martin Ho and Greg Maislin: The MDD Idea Exchange and Bayesian p-values
S00 Ep03 Pt2 with Martin Ho and Greg Maislin: Bayesian Methods and Digital Health Initiatives
S00 Ep03 with Martin Ho and Greg Maislin Pt 1: MDD Section Activities
S00 Ep02 with Emma Hughes: An Introduction to the IET Innovation Management Technical Network and Innovation in the NHS
S00 Ep01 Pt2: A Nifty Statistical Approach to Vital-Sign Artefact Detection
S00 Ep01 Pt 1: Gaussian Processes for Identifying the Deteriorating Patient
S00 Ep00 with Glen Wright Colopy: Welcome and hello!
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