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Foundations for a Probabilistic Theory of Causal Strength

Sprenger, Jan (2016) Foundations for a Probabilistic Theory of Causal Strength. [Preprint]

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Abstract

This paper develops axiomatic foundations for a probabilistic theory of causal strength. I proceed in three steps: First, I motivate the choice of causal Bayes nets as a framework for defining and comparing measures of causal strength. Second, I prove several representation theorems for probabilistic measures of causal strength---that is, I demonstrate how these measures can be derived from a set of plausible adequacy conditions. Third, I compare these measures on the basis of their characteristic properties, including an application to quantifying causal effect in medicine. Finally, I use the above results to argue for a specific measure of causal strength and I outline future research avenues.


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Item Type: Preprint
Creators:
CreatorsEmailORCID
Sprenger, Janj.sprenger@uvt.nl
Keywords: probabilistic causation; confirmation theory; philosophy of medicine; Bayesian networks; causal strength
Subjects: General Issues > Causation
Specific Sciences > Computer Science
General Issues > Confirmation/Induction
General Issues > Explanation
Specific Sciences > Medicine
Specific Sciences > Probability/Statistics
Depositing User: Jan Sprenger
Date Deposited: 18 Nov 2016 19:43
Last Modified: 18 Nov 2016 19:43
Item ID: 12644
Subjects: General Issues > Causation
Specific Sciences > Computer Science
General Issues > Confirmation/Induction
General Issues > Explanation
Specific Sciences > Medicine
Specific Sciences > Probability/Statistics
Date: 2016
URI: http://philsci-archive.pitt.edu/id/eprint/12644

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