Causal Inference Using Potential Outcomes

@article{Rubin2005CausalIU,
  title={Causal Inference Using Potential Outcomes},
  author={Donald B. Rubin},
  journal={Journal of the American Statistical Association},
  year={2005},
  volume={100},
  pages={322 - 331}
}
  • D. Rubin
  • Published 1 March 2005
  • Economics
  • Journal of the American Statistical Association
Causal effects are defined as comparisons of potential outcomes under different treatments on a common set of units. Observed values of the potential outcomes are revealed by the assignment mechanism—a probabilistic model for the treatment each unit receives as a function of covariates and potential outcomes. Fisher made tremendous contributions to causal inference through his work on the design of randomized experiments, but the potential outcomes perspective applies to other complex… 
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