Transitive reasoning distorts induction in causal chains

• Verfasst von: Sydow, Momme von [VerfasserIn]
• Verfasst von: Hagmayer, York [VerfasserIn]
• Verfasst von: Meder, Björn [VerfasserIn]
• Titel: Transitive reasoning distorts induction in causal chains
• Verf.angabe: Momme von Sydow, York Hagmayer, Björn Meder
• E-Jahr: 2016
• Jahr: [2016]
• Jahr des Originals: 2015
• Umfang: 19 S.
• Illustrationen: Illustrationen
• Fussnoten: Published online: 30 November 2015 ; Gesehen am 04.06.2020
• Titel Quelle: Enthalten in: Memory & cognition
• Ort Quelle: Heidelberg [u.a.] : Springer, 1973
• Jahr Quelle: 2016
• Band/Heft Quelle: 44(2016), 3, Seite 469-487
• ISSN Quelle: 1532-5946
• DOI: doi:10.3758/s13421-015-0568-5
• Datenträger: Online-Ressource
• Sprache: eng
• K10plus-PPN: 1699794596

Abstract

A probabilistic causal chain A→B→C may intuitively appear to be transitive: If A probabilistically causes B, and B probabilistically causes C, A probabilistically causes C. However, probabilistic causal relations can only guaranteed to be transitive if the so-called Markov condition holds. In two experiments, we examined how people make probabilistic judgments about indirect relationships A→C in causal chains A→B→C that violate the Markov condition. We hypothesized that participants would make transitive inferences in accordance with the Markov condition although they were presented with counterevidence showing intransitive data. For instance, participants were successively presented with data entailing positive dependencies A→B and B→C. At the same time, the data entailed that A and C were statistically independent. The results of two experiments show that transitive reasoning via a mediating event B influenced and distorted the induction of the indirect relation between A and C. Participants’ judgments were affected by an interaction of transitive, causal-model-based inferences and the observed data. Our findings support the idea that people tend to chain individual causal relations into mental causal chains that obey the Markov condition and thus allow for transitive reasoning, even if the observed data entail that such inferences are not warranted.