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Title: Individual differences in visual word recognition: Insights from the English Lexicon Project
Authors: Yap, M.J. 
Balota, D.A.
Sibley, D.E.
Ratcliff, R.
Keywords: Diffusion model
Ex-Gaussian analysis
Individual differences
Response time distributional analysis
Visual word recognition
Issue Date: Feb-2012
Citation: Yap, M.J., Balota, D.A., Sibley, D.E., Ratcliff, R. (2012-02). Individual differences in visual word recognition: Insights from the English Lexicon Project. Journal of Experimental Psychology: Human Perception and Performance 38 (1) : 53-79. ScholarBank@NUS Repository.
Abstract: Empirical work and models of visual word recognition have traditionally focused on group-level performance. Despite the emphasis on the prototypical reader, there is clear evidence that variation in reading skill modulates word recognition performance. In the present study, we examined differences among individuals who contributed to the English Lexicon Project (, an online behavioral database containing nearly 4 million word recognition (speeded pronunciation and lexical decision) trials from over 1,200 participants. We observed considerable within- and between-session reliability across distinct sets of items, in terms of overall mean response time (RT), RT distributional characteristics, diffusion model parameters (Ratcliff, Gomez, & Mckoon, 2004), and sensitivity to underlying lexical dimensions. This indicates reliably detectable individual differences in word recognition performance. In addition, higher vocabulary knowledge was associated with faster, more accurate word recognition performance, attenuated sensitivity to stimuli characteristics, and more efficient accumulation of information. Finally, in contrast to suggestions in the literature, we did not find evidence that individuals were trading-off their utilization of lexical and nonlexical information. © 2011 American Psychological Association.
Source Title: Journal of Experimental Psychology: Human Perception and Performance
ISSN: 00961523
DOI: 10.1037/a0024177
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