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。
| 教育研究における周辺構造モデル× | 傾向スコアマッチング× | |
|---|---|---|
| 分野≠ | 因果推論 | 研究統計 |
| 系統≠ | Regression model | Process / pipeline |
| 提唱年≠ | 2000 (method); 2006 (canonical education application) | 1983 |
| 提唱者≠ | James M. Robins, Miguel A. Hernán, Babette Brumback (epidemiology); Guanglei Hong & Stephen Raudenbush (education application) | Paul Rosenbaum and Donald Rubin |
| 種類≠ | Causal inference / weighted regression model | Method |
| 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 ↗ | Rosenbaum, P. R., & Rubin, D. B. (1983). The central role of the propensity score in observational studies for causal effects. Biometrika, 70(1), 41–55. DOI ↗ |
| 別名≠ | MSM, marginal structural model, MSM with inverse probability weighting, IPW-MSM | PSM, propensity score weighting, covariate balance |
| 関連≠ | 5 | 3 |
| 概要≠ | A marginal structural model (MSM) is a causal inference technique that uses inverse probability weighting to estimate the effect of a treatment or educational intervention that changes over time. Introduced by Robins, Hernán and Brumback (2000) in epidemiology and brought into education by Hong and Raudenbush (2006), MSMs handle time-varying confounding — a challenge that conventional regression cannot resolve. | Propensity score matching (PSM) is a method for reducing confounding bias in observational studies by balancing baseline characteristics between treatment groups, simulating randomization. Developed by Rosenbaum and Rubin (1983), it estimates the probability of receiving treatment given observed covariates, then matches or weights treated and control individuals with similar treatment probabilities. Widely used in medicine, epidemiology, and policy evaluation when randomized trials are infeasible or unethical, enabling estimation of treatment effects while controlling for selection bias. |
| ScholarGateデータセット ↗ |
|
|