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Peer-reviewedCC BY 4.0Integrative Psychological & Behavioral Science

Identifying Variable Relations Using Relevance Logic

  • Alexander von Eye1
  • Wolfgang Wiedermann2
  1. 1Michigan State University, 190 Allée du Nouveau Monde, 34000 Montpellier, France
  2. 2University of Missouri, Columbia, United States of America
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Abstract

In data analysis that is based on methods from the generalized linear model, variables are related to each other, and predictions are made in which variables are linked. Issues of discussion concern strength of relation and direction dependence. Relations are of the regression type. In this article, the discussion focuses on type of relation. Based on relevance logic, conjunctive, disjunctive and implicative relations are discussed, in particular with respect to their applicability in data analysis. It is illustrated how these relations can be distinguished from each other in cross-classifications of empirical data. It is also shown how predictions can be made of type of relation instead of variables themselves. Empirical data examples illustrate these predictions. Possible extensions are discussed in which relations of the type ‘if and only if’ are used.

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Cite

BibTeXRIS
BibTeX
@article{eye2026identifying,
  title = {{Identifying Variable Relations Using Relevance Logic}},
  author = {Alexander von Eye and Wolfgang Wiedermann},
  journal = {Integrative Psychological \& Behavioral Science},
  year = {2026},
  month = nov,
  doi = {10.1007/s12124-026-10034-z},
  url = {https://doi.org/10.1007/s12124-026-10034-z},
  note = {CC BY 4.0},
}
RIS
TY  - JOUR
TI  - Identifying Variable Relations Using Relevance Logic
AU  - Alexander von Eye
AU  - Wolfgang Wiedermann
PY  - 2026
DA  - 2026/11/04
JO  - Integrative Psychological & Behavioral Science
DO  - 10.1007/s12124-026-10034-z
UR  - https://doi.org/10.1007/s12124-026-10034-z
AB  - In data analysis that is based on methods from the generalized linear model, variables are related to each other, and predictions are made in which variables are linked. Issues of discussion concern strength of relation and direction dependence. Relations are of the regression type. In this article, the discussion focuses on type of relation. Based on relevance logic, conjunctive, disjunctive and implicative relations are discussed, in particular with respect to their applicability in data analysis. It is illustrated how these relations can be distinguished from each other in cross-classifications of empirical data. It is also shown how predictions can be made of type of relation instead of variables themselves. Empirical data examples illustrate these predictions. Possible extensions are discussed in which relations of the type ‘if and only if’ are used.
SN  - 1932-4502
SN  - 1936-3567
ER  -