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Measuring Causal Invariance Formally

Invariance is one of several dimensions of causal relationships within the interventionist account. The more invariant a relationship between two variables, the more the relationship should be considered paradigmatically causal. In this paper, I propose two formal measures to estimate invariance, il...

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Detalles Bibliográficos
Autor principal: Bourrat, Pierrick
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8228138/
https://www.ncbi.nlm.nih.gov/pubmed/34070711
http://dx.doi.org/10.3390/e23060690
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author Bourrat, Pierrick
author_facet Bourrat, Pierrick
author_sort Bourrat, Pierrick
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description Invariance is one of several dimensions of causal relationships within the interventionist account. The more invariant a relationship between two variables, the more the relationship should be considered paradigmatically causal. In this paper, I propose two formal measures to estimate invariance, illustrated by a simple example. I then discuss the notion of invariance for causal relationships between non-nominal (i.e., ordinal and quantitative) variables, for which Information theory, and hence the formalism proposed here, is not well suited. Finally, I propose how invariance could be qualified for such variables.
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spelling pubmed-82281382021-06-26 Measuring Causal Invariance Formally Bourrat, Pierrick Entropy (Basel) Article Invariance is one of several dimensions of causal relationships within the interventionist account. The more invariant a relationship between two variables, the more the relationship should be considered paradigmatically causal. In this paper, I propose two formal measures to estimate invariance, illustrated by a simple example. I then discuss the notion of invariance for causal relationships between non-nominal (i.e., ordinal and quantitative) variables, for which Information theory, and hence the formalism proposed here, is not well suited. Finally, I propose how invariance could be qualified for such variables. MDPI 2021-05-30 /pmc/articles/PMC8228138/ /pubmed/34070711 http://dx.doi.org/10.3390/e23060690 Text en © 2021 by the author. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Bourrat, Pierrick
Measuring Causal Invariance Formally
title Measuring Causal Invariance Formally
title_full Measuring Causal Invariance Formally
title_fullStr Measuring Causal Invariance Formally
title_full_unstemmed Measuring Causal Invariance Formally
title_short Measuring Causal Invariance Formally
title_sort measuring causal invariance formally
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8228138/
https://www.ncbi.nlm.nih.gov/pubmed/34070711
http://dx.doi.org/10.3390/e23060690
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