Journal Article

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

Clark Glymour

in The British Journal for the Philosophy of Science

Published on behalf of British Society for the Philosophy of Science

Volume 61, issue 1, pages 161-211
Published in print March 2010 | ISSN: 0007-0882
Published online November 2009 | e-ISSN: 1464-3537 | DOI: http://dx.doi.org/10.1093/bjps/axp039
What Is Right with ‘Bayes Net Methods’ and What Is Wrong with ‘Hunting Causes and Using Them’?

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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.

Introduction

Cartwright's Claims, and Their Errors

Problems of Causal Inference

Context

Graphical Causal Models and Markov Properties

Interventions, Experiments, and Randomization

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

Cartwright's Objections Again

Conclusion

Journal Article.  18671 words.  Illustrated.

Subjects: Philosophy of Science ; Science and Mathematics

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