G-methods for time-varying treatments (Causal inference: What if, Chapter 21-1)

Keywords: 因果推論, Time-varying, G-formula, IP weighting, Doubly robust estimation

Transcript

2. ・G-methods for time-fixed treatments 本日の内容 ・The g-formula for time-varying treatments ・IP weighting for time-varying treatments ・A doubly robust estimator for time-varying treatments
3. ・G-methods for time-fixed treatments 本日の内容 ・The g-formula for time-varying treatments ・IP weighting for time-varying treatments ・A doubly robust estimator for time-varying treatments
4. Stratification effect measure modification (-) effect measure modification (+) Mantel-Haenszel method 別々にオッズ比を報告
5. Why model? effect measure modification (-) effect measure modification (+) 別々にオッズ比を報告（1つの効果を報告できない） g-methods
6. g-formula A=1を代入 A=0を代入
7. IP weighting marginal structural model
8. Conditional or Marginal? outcome regression saturated parametric stratification g-formula IP weighting g-estimation or algebraically equivalent
9. Time-varying treatment g-methods
10. ・G-methods for time-fixed treatments 本日の内容 ・The g-formula for time-varying treatments ・IP weighting for time-varying treatments ・A doubly robust estimator for time-varying treatments
11. 前提 ・本章ではidentifiability conditions(sequential exchangeability, positivity, and consistency)のviolationが ないものとする。 ・static treatment strategies (always treat vs. never treat) の効果を推定する。
12. g-formula (weighted average) ・time-fixed treatment (A1 の反実アウトカム) ・time-varying treatment
13. g-formula (weighted average)
14. g-formula (weighted average)
15. g-formula (simulation) のシミュレーション と
16. g-formulaの注意点 ・DAGに基づいたcovariates L1 をモデルに含める ・static sequential exchangeabilityが成立すればstatic treatment strategyの効果はidentify可能
17. g-formulaの一般化 ・static treatment strategy ・dynamic treatment strategy linear regression logistic regression
18. ・G-methods for time-fixed treatments 本日の内容 ・The g-formula for time-varying treatments ・IP weighting for time-varying treatments ・A doubly robust estimator for time-varying treatments
19. IP weighting (weights) ・nonstabilized IP weights ・ stabilized IP weights
20. IP weighting (non-stabilized)
21. Stabilized weights non-stabilized weights: stabilized weights: Lと独立であればよい Lと独立であればよい
22. IP weighting (stabilized)
23. IP weightingの一般化 ・nonstabilized IP weights ・ stabilized IP weights logistic regression logistic regression （misspecifiedでも可）
24. Marginal Structural Model ・2K > Nのときは推定できない ・marginal structural mean model stabilized IP weightsを使って推定 misspecified??
25. Effect Measure Modification ・baseline variable VによるEMMがある場合、marginal structural modelは以下の通り（parametric） stabilized IP weightsを使って推定 Vに入れて良いのはbaseline variableだけ
26. ・G-methods for time-fixed treatments 本日の内容 ・The g-formula for time-varying treatments ・IP weighting for time-varying treatments ・A doubly robust estimator for time-varying treatments
27. Doubly Robust Estimator ・g-formula ・ IP weighting
28. 1. Doubly Robust (time-fixed) 2. 3. A=1とA=0でそれぞれ を推定 を推定 , をLについて標準化
29. 1. Doubly Robust (time-varying) 2. 3. を推定 からパラメータ を求める。 を求めておく を推定し、Aの値に応じた を求める。 これを繰り返して を求める。 always treat
30. Discussion