Chapter 17 Causal Surivival analysis（『Causal Inference: What If』勉強会）

Chapter 19 Time-varying treatments（『Causal Inference: What If』勉強会）

Chapter 11 Why model?（『Causal Inference: What If』勉強会）

Chapter 20 Treatment-confounder feedback（『Causal Inference: What If』勉強会）

Chapter 14 G-estimation of structural nested models（『Causal Inference: What If』勉強会）

Chapter 18 Variable selection for causal inference（『Causal Inference: What If』勉強会）

Chapter 22 Target trial emulation（『Causal Inference: What If』勉強会）

Jessica Young: Causal inference with competing events

Vanessa Didelez: 生存および事象発生までの時間分析における因果推論

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Caleb Miles: Two fundamental problems in causal mediation analysis

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Fabrizia Mealli: Bayesian causal inference: a potential outcome perspective with applications to...

Susan Athey と Stefan Wager: R における不均一な治療効果の推定

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Introduction to Causal Inference and Directed Acyclic Graphs

1. 現実世界のデータに基づく因果推論のためのターゲットを絞った機械学習

Causal Inference & Clinical Trials: Myths of Randomization | Stephen Senn | CausalBanditsPodcast.com

Stijn Vansteelandt: Assumption-lean Causal Modeling