Optimal cue aggregation in the absence of criterion knowledge

The study of multi‐cue judgment investigates how decision makers aggregate cues to predict the value of a criterion variable. We consider a multi‐cue judgment task in which decision makers have prior knowledge of inter‐cue relationships but are ignorant of how the cues correlate with the criterion....

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Bibliographic Details
Published in:Journal of behavioral decision making 2019-10, Vol.32 (4), p.415-430
Main Authors: Zhao, Wenjia Joyce, Davis‐Stober, Clintin P., Bhatia, Sudeep
Format: Article
Language:English
Subjects:
cue integration
Cues
Decision makers
Decision making
dimensionality reduction
improper linear models
judgment and decision making
Mental task performance
Prior knowledge
Weighting
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Summary:The study of multi‐cue judgment investigates how decision makers aggregate cues to predict the value of a criterion variable. We consider a multi‐cue judgment task in which decision makers have prior knowledge of inter‐cue relationships but are ignorant of how the cues correlate with the criterion. In this setting, a naive judgment strategy prescribes weighting the cues equally. Although many participants are well described via an equal weighting scheme, we find that a substantial minority of participants make predictions consistent with a weighting scheme based on a low‐dimensional projection of the cue space that optimally takes into account inter‐cue correlations. The use of such a weighting scheme is consistent with minimizing maximal error in prediction when the cue‐criterion relationships are unknown.
ISSN:0894-3257
1099-0771
DOI:10.1002/bdm.2123