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

Transcript

1. None

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