کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
920259 920274 2010 10 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
A probabilistic threshold model: Analyzing semantic categorization data with the Rasch model
موضوعات مرتبط
علوم زیستی و بیوفناوری علم عصب شناسی علوم اعصاب شناختی
پیش نمایش صفحه اول مقاله
A probabilistic threshold model: Analyzing semantic categorization data with the Rasch model
چکیده انگلیسی

According to the Threshold Theory (Hampton, 1995, 2007) semantic categorization decisions come about through the placement of a threshold criterion along a dimension that represents items' similarity to the category representation. The adequacy of this theory is assessed by applying a formalization of the theory, known as the Rasch model (Rasch, 1960; Thissen & Steinberg, 1986), to categorization data for eight natural language categories and subjecting it to a formal test. In validating the model special care is given to its ability to account for inter- and intra-individual differences in categorization and their relationship with item typicality. Extensions of the Rasch model that can be used to uncover the nature of category representations and the sources of categorization differences are discussed.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Acta Psychologica - Volume 135, Issue 2, October 2010, Pages 216–225
نویسندگان
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