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. (shrink)

The utility of an “ecologically rational” recognition‐based decision rule in multichoice decision problems is analyzed, varying the type of judgment required (greater or lesser). The maximum size and range of a counterintuitive advantage associated with recognition‐based judgment (the “less‐is‐more effect”) is identified for a range of cue validity values. Greater ranges of the less‐is‐more effect occur when participants are asked which is the greatest of m choices (m > 2) than which is the least. Less‐is‐more effects also have greater range (...) for larger values of m. This implies that the classic two‐alternative forced choice task, as studied by, may not be the most appropriate test case for less‐is‐more effects. (shrink)

Motivated by accounts of concept use in autistic spectrum disorder (ASD) and a computational model of weak central coherence (O'Loughlin and Thagard, 2000) we examined comprehension and production vocabulary in typically-developing children and those with ASD and Down syndrome (DS). Controlling for frequency, familiarity, length and imageability, Colorado Meaningfulness played a hitherto unremarked role in the vocabularies of children with ASD. High Colorado Meaningful words were underrepresented in the comprehension vocabularies of 2- to 12-year-olds with ASD. The Colorado Meaningfulness of (...) a word is a measure of how many words can be associated with it. Situations in which high Colorado Meaningfulness words are encountered are typically highly variable, and words with High Colorado Meaningfulness often involve extensive use of context. Our data suggest that the number of contexts in which a particular word can appear has a role in determining vocabulary in ASD. This suggestion is consistent with the weak central coherence theory of autism. (shrink)