Andersen, Holly (2023) Why adoption of causal modeling methods requires some metaphysics. [Preprint]
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Andersen preprint routledge chapter causal metaphysics for modelling FINAL.pdf Download (187kB) | Preview |
Abstract
I highlight a metaphysical concern that stands in the way of more widespread adoption of causal modeling techniques such as causal Bayes nets. Researchers in some fields may resist adoption due to concerns that they don't 'really' understand what they are saying about a system when they apply such techniques. Students in these fields are repeated exhorted to be cautious about application of statistical techniques to their data without a clear understanding of the conditions required for those techniques to yield genuine insight into the data. They are acutely aware that anyone can chuck some data into a software package and get what looks like an answer, even though these tests may not be well-defined for the data on which they can apparently be run. This is thus a healthy skepticism for uptake of causal modeling methods, which points directly to the need for a metaphysical understanding of causation in order to successfully use the modeling methods. Without a clear understanding of what the methods are committing to, including what it means to say that there exists a causal relationship, researchers have limited ability to identify potentially bad output, or to independently verify results.
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Item Type: | Preprint | ||||||
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Additional Information: | forthcoming in Federica Russo and Phyllis Ilari, (eds.), Routledge Handbook of Causality and Causal Methods,. Routledge | ||||||
Keywords: | Causal Markov, Causal Faithfulness, causal Bayes nets, modelling, metaphysics | ||||||
Subjects: | General Issues > Scientific Metaphysics General Issues > Causation General Issues > Explanation Specific Sciences > Medicine > Health and Disease |
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Depositing User: | Dr. Holly Andersen | ||||||
Date Deposited: | 20 Sep 2023 11:28 | ||||||
Last Modified: | 20 Sep 2023 11:28 | ||||||
Item ID: | 22562 | ||||||
Subjects: | General Issues > Scientific Metaphysics General Issues > Causation General Issues > Explanation Specific Sciences > Medicine > Health and Disease |
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Date: | 2023 | ||||||
URI: | https://philsci-archive.pitt.edu/id/eprint/22562 |
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