Linear Models: A Useful “Microscope” for Causal Analysis

Pearl Judea ()
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Pearl Judea: Department of Computer Science, University of California Los Angeles, Los Angeles, CA, USA

Journal of Causal Inference, 2013, vol. 1, issue 1, 155-170

Abstract: This note reviews basic techniques of linear path analysis and demonstrates, using simple examples, how causal phenomena of non-trivial character can be understood, exemplified and analyzed using diagrams and a few algebraic steps. The techniques allow for swift assessment of how various features of the model impact the phenomenon under investigation. This includes: Simpson’s paradox, case–control bias, selection bias, missing data, collider bias, reverse regression, bias amplification, near instruments, and measurement errors.

Keywords: structural equation model; linear model; path analysis (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:bpj:causin:v:1:y:2013:i:1:p:155-170:n:6

DOI: 10.1515/jci-2013-0003

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