Structural equation modelling of human judgement

Thinking and Reasoning 7 (1):51 – 68 (2001)
Abstract
Structural equation modelling (SEM) is outlined and compared with two non-linear alternatives, artificial neural networks and ''fast and frugal'' models. One particular non-linear decision-making situation is discussed, that exemplified by a lexicographic semi-order. We illustrate the use of SEM on a dataset derived from 539 volunteers' responses to questions about food-related risks. Our conclusion is that SEM is a useful member of the armoury of techniques available to the student of human judgement: it subsumes several multivariate statistical techniques and permits their flexible combination, and it provides robust goodness-of-fit statistics and is available in (generally) easy-to-use computer packages. Although the number of tasks for which SEM provides a persuasive psychological model is small, it is very useful in identifying the important variables and their inter-relations that contribute to task performance, and thus can constitute a valuable intermediate staging point between raw data and a fully fledged psychological theory.
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