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2012

2012

We present methods able to predict the presence and strength of conditional and unconditional dependencies (correlations) between… Expand

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Highly Cited

2010

Highly Cited

2010

Inferring the causal structure that links n observables is usually based upon detecting statistical dependences and choosing… Expand

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2010

2010

The causal Markov condition (CMC) is a postulate that links observations to causality. It describes the conditional independences… Expand

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2006

2006

Hausman & Woodward present an argument for the Causal Markov Condition (CMC) on the basis of a principle they dub 'modularity… Expand

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2005

2005

The causal Markov condition (CMC) plays an important role in much recent work on the problem of causal inference from statistical… Expand

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2004

2004

This paper explores the relationship between a manipulability conception of causation and the causal Markov condition (CM). We… Expand

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2004

2004

In this article I propose a logic that allows one to derive causal statements from probabilistic information. Of course, since… Expand

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Highly Cited

2002

Highly Cited

2002

In their rich and intricate paper 'Independence, Invariance, and the Causal Markov Condition', Daniel Hausman and James Woodward… Expand

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Highly Cited

1999

Highly Cited

1999

This essay explains what the Causal Markov Condition says and defends the condition from the many criticisms that have been… Expand

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1996

1996

This paper provides a priori cirteria for determing when a causal model is sufficiently complete to be considered a Bayesian… Expand

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