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A diffusion decision model analysis of evidence variability in the lexical decision task

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posted on 2023-05-19, 02:12 authored by Tillman, G, Osth, AF, van Ravenzwaaij, D, Heathcote, A
The lexical-decision task is among the most commonly used paradigms in psycholinguistics. In both the signal-detection theory and Diffusion Decision Model (DDM; Ratcliff, Gomez, & McKoon, Psychological Review, 111, 159–182, 2004) frameworks, lexical-decisions are based on a continuous source of word-likeness evidence for both words and non-words. The Retrieving Effectively from Memory model of Lexical-Decision (REM–LD; Wagenmakers et al., Cognitive Psychology, 48(3), 332–367, 2004) provides a comprehensive explanation of lexical-decision data and makes the prediction that word-likeness evidence is more variable for words than non-words and that higher frequency words are more variable than lower frequency words. To test these predictions, we analyzed five lexical-decision data sets with the DDM. For all data sets, drift-rate variability changed across word frequency and non-word conditions. For the most part, REM–LD’s predictions about the ordering of evidence variability across stimuli in the lexical-decision task were confirmed.

History

Publication title

Psychonomic Bulletin and Review

Volume

24

Issue

6

Pagination

1949-1956

ISSN

1069-9384

Department/School

School of Psychological Sciences

Publisher

Psychonomic Soc Inc

Place of publication

United States

Rights statement

Copyright 2017 Psychonomic Society, Inc. This is a post-peer-review, pre-copyedit version of an article published in Psychonomic bulletin and review. The final authenticated version is available online at: http://dx.doi.org/10.3758/s13423-017-1259-y

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  • Restricted

Socio-economic Objectives

Expanding knowledge in psychology

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