Causal inferences as perceptual judgements

Area of Science:

• Cognitive Psychology
• Causal Inference

Background:

• Human causal judgments are fundamental to decision-making.
• Understanding how individuals process contingency information is key to cognitive science.

Purpose of the Study:

• To investigate how people make causal judgments based on contingency information.
• To compare causal judgment strategies in discrete and continuous paradigms.

Main Methods:

• Analysis of causal judgments in discrete and continuous experimental paradigms.
• Subjects evaluated contingency information presented as frequencies (discrete) or rates (continuous).
• Comparison of subject responses to probability (P1, P2, delta P) and rate-based models.

Main Results:

• In the discrete paradigm, subjects used either P1 or delta P (P1-P2) models, or a combination.
• Subject reports accurately reflected their chosen judgment model.
• The weighted delta P model effectively fit combined subject data.
• In the continuous paradigm, judgments were based on event rates, not probabilities.

Conclusions:

• Causal judgments are influenced by the experimental paradigm (discrete vs. continuous).
• Perceptually salient variables significantly impact causal ratings.
• Individuals employ distinct strategies for processing contingency information in causal inference.