Causal Inference in the Presence of Latent Variables and Selection Bias

📝 Original Info

• Title: Causal Inference in the Presence of Latent Variables and Selection Bias
• ArXiv ID: 1302.4983
• Date: 2013-02-21
• Authors: Researchers from original ArXiv paper

📝 Abstract

We show that there is a general, informative and reliable procedure for discovering causal relations when, for all the investigator knows, both latent variables and selection bias may be at work. Given information about conditional independence and dependence relations between measured variables, even when latent variables and selection bias may be present, there are sufficient conditions for reliably concluding that there is a causal path from one variable to another, and sufficient conditions for reliably concluding when no such causal path exists.

💡 Deep Analysis

Deep Dive into Causal Inference in the Presence of Latent Variables and Selection Bias.

We show that there is a general, informative and reliable procedure for discovering causal relations when, for all the investigator knows, both latent variables and selection bias may be at work. Given information about conditional independence and dependence relations between measured variables, even when latent variables and selection bias may be present, there are sufficient conditions for reliably concluding that there is a causal path from one variable to another, and sufficient conditions for reliably concluding when no such causal path exists.

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