- Title
- A diffusion decision model analysis of evidence variability in the lexical decision task
- Creator
- Tillman, Gabriel; Osth, Adam F.; van Ravenzwaaij, Don; Heathcote, Andrew
- Relation
- Psychonomic Bulletin and Review Vol. 24, Issue 6, p. 1949-1956
- Publisher Link
- http://dx.doi.org/10.3758/s13423-017-1259-y
- Publisher
- Springer
- Resource Type
- journal article
- Date
- 2017
- Description
- 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.
- Subject
- lexical-decision task; diffusion decision model; REM-LD
- Identifier
- http://hdl.handle.net/1959.13/1386180
- Identifier
- uon:32373
- Identifier
- ISSN:1069-9384
- Language
- eng
- Reviewed
- Hits: 1329
- Visitors: 1509
- Downloads: 0
Thumbnail | File | Description | Size | Format |
---|