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 | ||||||
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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 |
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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 |
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Date: | 2016 | ||||||
URI: | https://philsci-archive.pitt.edu/id/eprint/12644 |
Available Versions of this Item
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Foundations for a Probabilistic Theory of Causal Strength. (deposited 25 Feb 2016 04:04)
- Foundations for a Probabilistic Theory of Causal Strength. (deposited 18 Nov 2016 19:43) [Currently Displayed]
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