Recovering from Selection Bias in Causal and Statistical Inference

@article{Bareinboim2014RecoveringFS,
  title={Recovering from Selection Bias in Causal and Statistical Inference},
  author={Elias Bareinboim and Jin Tian and Judea Pearl},
  journal={Probabilistic and Causal Inference},
  year={2014}
}
Selection bias is caused by preferential exclusion of units from the samples and represents a major obstacle to valid causal and statistical inferences; it cannot be removed by randomized experiments and can rarely be detected in either experimental or observational studies. In this paper, we provide complete graphical and algorithmic conditions for recovering conditional probabilities from selection biased data. We also provide graphical conditions for recoverability when unbiased data is… 

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