Chapter

Heuristic and Linear Models of Judgment: Matching Rules and Environments

Robin M. Hogarth and Natalia Karelaia

in Heuristics

Published in print April 2011 | ISBN: 9780199744282
Published online May 2011 | e-ISBN: 9780199894727 | DOI: http://dx.doi.org/10.1093/acprof:oso/9780199744282.003.0013
Heuristic and Linear Models of Judgment: Matching Rules and Environments

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Much research has highlighted incoherent implications of judgmental heuristics, yet other findings have demonstrated high correspondence between predictions and outcomes. At the same time, judgment has been well modeled in the form of as if linear models. Accepting the probabilistic nature of the environment, the chapter uses statistical tools to model how the performance of heuristic rules varies as a function of environmental characteristics. They further characterize the human use of linear models by exploring effects of different levels of cognitive ability. The chapter illustrates with both theoretical analyses and simulations. Results are linked to the empirical literature by a meta-analysis of lens model studies. Using the same tasks, the chapter gives an estimation of the performance of both heuristics and humans where the latter are assumed to use linear models. The results emphasize that judgmental accuracy depends on matching characteristics of rules and environments and highlight the trade-off between using linear models and heuristics. Whereas the former can be cognitively demanding, the latter are simple to implement. However, heuristics require knowledge to indicate when they should be used.

Keywords: decision making; heuristics; linear models; lens model; judgmental biases

Chapter.  15125 words.  Illustrated.

Subjects: Cognitive Psychology

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