ScholarGate
アシスタント

手法を比較

選択した手法を並べて確認できます。異なる行はハイライト表示されます。

政策評価のための周辺構造モデル×逆確率重み付け法 (IPW / IPTW)×
分野因果推論因果推論
系統Regression modelRegression model
提唱年20002000
提唱者James M. Robins, Miguel A. Hernan, Babette BrumbackRobins, Hernán & Brumback
種類Causal inference / weighted regressionCausal inference weighting estimator
原典Robins, J. M., Hernan, M. A., & Brumback, B. (2000). Marginal structural models and causal inference in epidemiology. Epidemiology, 11(5), 550–560. DOI ↗Robins, J. M., Hernán, M. A., & Brumback, B. (2000). Marginal Structural Models and Causal Inference in Epidemiology. Epidemiology, 11(5), 550-560. DOI ↗
別名MSM for policy evaluation, policy MSM, causal MSM, structural policy weighting modelIPW, IPTW, inverse probability of treatment weighting, marginal structural model weighting
関連65
概要A Policy Evaluation Marginal Structural Model (MSM) is a causal inference framework that estimates the population-average effect of a policy by using inverse probability weighting to create a pseudo-population in which treatment assignment is independent of measured confounders, enabling unbiased comparison of potential outcomes under different policy scenarios from observational data.Inverse Probability Weighting is a causal-inference method that assigns each observation a weight equal to the inverse of its probability of receiving the treatment it actually received. Introduced by Robins, Hernán and Brumback (2000) for marginal structural models, it builds a pseudo-population in which treatment is independent of measured confounders, balancing selection bias.
ScholarGateデータセット
  1. v1
  2. 2 出典
  3. PUBLISHED
  1. v1
  2. 2 出典
  3. PUBLISHED

検索へ スライドをダウンロード

ScholarGate手法を比較: Policy Evaluation Marginal Structural Model · Inverse Probability Weighting. 2026-06-18に以下より取得 https://scholargate.app/ja/compare