eCite Digital Repository

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


Tillman, G and Osth, AF and van Ravenzwaaij, D and Heathcote, A, A diffusion decision model analysis of evidence variability in the lexical decision task, Psychonomic Bulletin and Review, 24, (6) pp. 1949-1956. ISSN 1069-9384 (2017) [Refereed Article]


Copyright 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:

DOI: doi:10.3758/s13423-017-1259-y


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.

Item Details

Item Type:Refereed Article
Keywords:lexical-decision task, diffusion decision model, REM-LD
Research Division:Psychology
Research Group:Cognitive and computational psychology
Research Field:Memory and attention
Objective Division:Expanding Knowledge
Objective Group:Expanding knowledge
Objective Field:Expanding knowledge in psychology
UTAS Author:Heathcote, A (Professor Andrew Heathcote)
ID Code:114614
Year Published:2017
Web of Science® Times Cited:4
Deposited By:Psychology
Deposited On:2017-02-22
Last Modified:2018-08-27
Downloads:84 View Download Statistics

Repository Staff Only: item control page