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  1.  62
    Structural equation modelling of human judgement.Philip T. Smith, Frank McKenna, Claire Pattison & Andrea Waylen - 2001 - Thinking and Reasoning 7 (1):51 – 68.
    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 (...)
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  2.  37
    Which Words are Hard for Autistic Children to Learn?Graham Schafer, Tim I. Williams & Philip T. Smith - 2013 - Mind and Language 28 (5):661-698.
    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 (...)
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  3.  29
    The Relative Success of Recognition‐Based Inference in Multichoice Decisions.Rachel McCloy, C. Philip Beaman & Philip T. Smith - 2008 - Cognitive Science 32 (6):1037-1048.
    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 (...)
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