Mathematics
3 years ago

New method accurately measures impact of Beijing pollution on health outcomes.

Propensity Score Matching on Discrete Treatment: Beijing Pm2.5 Case Study
Jie Hou, Shaofei Shen, Jing Wang, Siqi Xu, Yijing Liu

Paper Summary

The article explores how different levels of treatment affect outcomes using a method called propensity score matching. This method helps estimate the impact of treatment on results in areas like medicine and economics. The researchers used machine learning models to estimate treatment effects in the Beijing pm 2.5 dataset.

Related papers

Theme background image
Mathematics
2 years ago

New method reveals true impact of treatment odds on patient outcomes.

Causal Inference
Education Inequality
Theme background image
Mathematics
3 years ago

New method accurately measures impact of Beijing pollution on health outcomes.

Causal Inference
Regularization Methods
Missing Data
1 view
Theme background image
Mathematics
5 years ago

Privatising Propensity Scores Safeguards Sensitive Data in Causal Analysis.

Causal Inference
Regularization Methods
Missing Data
1 view