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Related Experiment Video

Updated: Apr 4, 2026

Task Interruption and Resumption Paradigm for Testing the Activation and Pursuit of an Abstract Thinking Goal

Task Interruption and Resumption Paradigm for Testing the Activation and Pursuit of an Abstract Thinking Goal

Published on: April 18, 2017

How multiple causes combine: independence constraints on causal inference.

Mimi Liljeholm¹

¹Department of Cognitive Sciences, University of California Irvine, CA, USA.

Frontiers in Psychology

|September 1, 2015

Summary

Uncertainty in causal relationships increases when causes are confounded or interact. This study confirms the causal power view, showing how violations of independence impact causal induction and strength estimation.

Keywords:

Bayesian inference causal power confounding interaction uncertainty

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Last Updated: Apr 4, 2026

Task Interruption and Resumption Paradigm for Testing the Activation and Pursuit of an Abstract Thinking Goal

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Published on: April 18, 2017

Exploring the Role of Deontic Reasoning and World Knowledge in Wason´s Selection Task

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Published on: July 22, 2025

Area of Science:

Cognitive Psychology
Causal Inference
Decision Making

Background:

The causal power view posits that independent causes and independent influences are crucial for accurate causal induction.
Violations of these independence constraints can introduce uncertainty regarding causal relationships.

Purpose of the Study:

To investigate how confounding and interaction between candidate causes affect uncertainty in causal induction.
To test the predictions of the causal power view regarding these violations.

Main Methods:

Participants evaluated causal relationships under conditions of confounding and/or interaction between candidate causes.
Experimental design manipulated the independence of candidate causes and their influences.

Main Results:

Increased uncertainty about causal existence and strength was observed when causes were confounded or interacted.
A Bayesian causal model accounted for uncertainty arising from confounding but not interaction.

Conclusions:

Confounding and interaction significantly increase uncertainty in causal judgments, supporting the causal power view.
Distinct mechanisms may underlie uncertainty generated by confounding versus interaction, impacting causal generalization.