Propensity score weighting under limited overlap and model misspecification

@article{Zhou2020PropensitySW,
  title={Propensity score weighting under limited overlap and model misspecification},
  author={Yunji Zhou and Roland A. Matsouaka and Laine E Thomas},
  journal={Statistical Methods in Medical Research},
  year={2020},
  volume={29},
  pages={3721 - 3756}
}
Propensity score weighting methods are often used in non-randomized studies to adjust for confounding and assess treatment effects. The most popular among them, the inverse probability weighting, assigns weights that are proportional to the inverse of the conditional probability of a specific treatment assignment, given observed covariates. A key requirement for inverse probability weighting estimation is the positivity assumption, i.e. the propensity score must be bounded away from 0 and 1. In… 

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