Casini, Lorenzo and Moneta, Alessio and Capasso, Marco (2020) Variable Definition and Independent Components. In: UNSPECIFIED.

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Abstract

In the causal modelling literature, it is well known that “ill-defined” variables may give rise to “ambiguous manipulations” (Spirtes and Scheines, 2004). Here, we illustrate how ill-defined variables may also induce mistakes in causal inference when standard causal search methods are applied (Spirtes et al., 2000; Pearl, 2009). To address the problem, we introduce a representation framework, which exploits an independent component representation of the data, and demonstrate its potential for detecting ill-defined variables and avoiding mistaken causal inferences.

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Item Type:	Conference or Workshop Item (UNSPECIFIED)
Creators:	Creators Email ORCID Casini, Lorenzo lorenzo.casini@unige.ch 0000-0001-9891-7324 Moneta, Alessio a.moneta@santannapisa.it Capasso, Marco marco.capasso@gmail.com
Additional Information:	Accepted for publication in the PSA2020 proceedings. [2020] PSA2020: The 27th Biennial Meeting of the Philosophy of Science Association (Baltimore, MD; 18-22 Nov 2020)
Subjects:	General Issues > Causation
Depositing User:	Dr. Lorenzo Casini
Date Deposited:	07 Jul 2020 02:12
Last Modified:	09 Jul 2020 14:07
Item ID:	17438
Subjects:	General Issues > Causation
Date:	2 July 2020
URI:	https://philsci-archive.pitt.edu/id/eprint/17438

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