title: Inferring children's categorizations from sequential touching behaviors: an analytical model.
abstract: A child is assumed to belong to 1 of 2 classes: categorizer or noncategorizer. To determine which, 4 toy animals and 4 toy vehicles were randomly arrayed for touching for 2 min. The task was to infer whether the child was a categorizer or a noncategorizer for vehicles and similarly for animals. A model is proposed that assumes a child's sequence of touches follows one probability distribution if the child is a categorizer and another distribution if the child is a noncategorizer. The proportion of children in each category and the probability of a child being a categorizer for, say, vehicles are among the quantities that can be estimated. Data from 18-month-old children are illustrative. The model appears efficient and robust.
authors.affiliation: Department of Psychology, Pennsylvania State University, University Park 16802-3105, USA. hxt@psu.edu
authors.forename: H
authors.initials: H
authors.lastname: Thomas
authors.forename: M P
authors.initials: MP
authors.lastname: Dahlin
mesh_terms: D002657:Child Development / Q000502:physiology; D003210:Concept Formation; D005260:Female; D006801:Humans; D007223:Infant; D018730:Infant Behavior / Q000523:psychology; D008297:Male; D008960:Models, Psychological; D002666:Psychology, Child; D011897:Random Allocation; D014110:Touch / Q000502:physiology*