Recovering from Selection Bias in Causal and Statistical Inference مقاله هوش مصنوعی 2014

Abstract 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, weprovide complete graphical and algorithmic conditions forrecovering conditional probabilities from selection biaseddata. We also provide graphical conditions for recoverabilitywhen unbiased data is ...