Regression modelQuasi-experimental / causal inference
政策评估倾向得分加权
政策评估倾向得分加权将逆概率加权应用于观测数据,以估计政策项目中的因果效应。通过重新加权参与者和非参与者,使他们与目标人群相似,从而消除了自愿或行政分配项目中的选择偏差,而无需随机化。
在 MethodMind 中打开即将推出Apply, compare, get guidance
Tools & resources
Learn & explore
视频即将推出
阅读完整方法
仅限会员
登录使用免费账户登录即可阅读本节。
方法图谱
相关方法的邻域——选择一个节点以展开探索。
来源
- Hirano, K., Imbens, G. W., & Ridder, G. (2003). Efficient Estimation of Average Treatment Effects Using the Estimated Propensity Score. Econometrica, 71(4), 1161-1189. DOI: 10.1111/1468-0262.00442 ↗
- Caliendo, M., & Kopeinig, S. (2008). Some Practical Guidance for the Implementation of Propensity Score Matching. Journal of Economic Surveys, 22(1), 31-72. DOI: 10.1111/j.1467-6419.2007.00527.x ↗
如何引用本页
ScholarGate. (2026, June 3). Propensity Score Weighting for Policy Evaluation. ScholarGate. https://scholargate.app/zh/causal-inference/policy-evaluation-propensity-score-weighting
选用哪种方法?
将本方法与其最相近的同类并置,并排研读——本馆将书籍铺陈于案上,取舍则由您定夺。
- 双重差分法 (Diff-in-Diff)计量经济学↔ 比较
- 双重稳健估计(AIPW)因果推断↔ 比较
- 逆概率治疗加权法 (IPW / IPTW)因果推断↔ 比较
- 政策评估双重差分法因果推断↔ 比较
- 倾向得分匹配研究统计学↔ 比较
- 倾向得分加权法 (PSW / IPW)因果推断↔ 比较
Similar methods
Policy Evaluation Inverse Probability WeightingPropensity Score WeightingPolicy Evaluation Propensity Score MatchingRobust Propensity Score WeightingPanel Data Propensity Score WeightingPropensity Score Weighting in Education ResearchRobust Inverse Probability WeightingPolicy Evaluation Doubly Robust Estimation