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The British Journal for the Philosophy of Science Advance Access published online on November 12, 2009
The British Journal for the Philosophy of Science, doi:10.1093/bjps/axp039
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© The Author (2009). Published by Oxford University Press on behalf of British Society for the Philosophy of Science. All rights reserved. For permissions, please email: journals.permissions@oxfordjournals.org

What Is Right with ‘Bayes Net Methods’ and What Is Wrong with ‘Hunting Causes and Using Them’?

Clark Glymour

Carnegie Mellon University, Pittsburgh, PA 15213, USA Institute for Human and Machine Cognition Pensacola, FL 32507, USA cg09{at}andrew.cmu.edu


  Abstract

Nancy Cartwright's recent criticisms of efforts and methods to obtain causal information from sample data using automated search are considered. In addition to reviewing that effort, I argue that almost all of her criticisms are false and rest on misreading, overgeneralization, or neglect of the relevant literature.

  1. Introduction
  2. Cartwright's Claims, and Their Errors
  3. Problems of Causal Inference
  4. Context
  5. Graphical Causal Models and Markov Properties
  6. Interventions, Experiments, and Randomization
  7. Search for Causal Explanations
    7.1 The PC algorithm
    7.2 The Fast Causal Inference algorithm
    7.3 ION and iMAGES
    7.4 Build pure clusters and MimBuild
    7.5 Measurement error and mixed methods
    7.6 Time series
    7.7 LiNGAM

  8. Cartwright's Objections Again
  9. Conclusion


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