A diffusion model account of the lexical decision task.

By Roger Ratcliff, Pablo Gómez, Gail McKoon. Psychology Review, 2004

573 citations recorded by the source corpus.

Subfields: Cognitive Neuroscience, Developmental and Educational Psychology

View Paper: https://www.semanticscholar.org/paper/cc11cda974c76e07c125c2745816919a23e8aec0

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Citations in the corpus

The Bayesian reader: explaining word recognition as an optimal Bayesian decision process. (2006, background): “In recent years, a number of researchers have also performed analyses of RT distributions in lexical decision and naming (Andrews & Heathcote, 2001; Balota & Spieler, 1999; Grainger & Jacobs, 1996; Ratcliff et al., 2004).”
Methodological and empirical developments for the Ratcliff diffusion model of response times and accuracy (2009, methodology): “The deadline model for lexical decision is radically different from the diffusion model for lexical decision (Ratcliff et al., 2004a; Yap, Balota, Cortese, & Watson, 2006).”
Morality shifting in the context of intergroup violence (2012, methodology): “Our analytical strategy is also in line with literature on data transformation in general (e.g., Tabachnick & Fidell, 2007) and handling of reaction time data in particular (e.g., Norris 2009; Ratcliff et al., 2004).”
The Diffusion Decision Model: Theory and Data for Two-Choice Decision Tasks (2008, methodology): “To avoid errors, they set their decision criteria significantly further from the starting point of the decision process than young adults do. Counter to the previously held view, in most tasks, the qualityoftheinformationonwhichdecisionsarebased(i.e.,driftrate)isnot significantly worse for the older”
Improved matrix reasoning is limited to training on tasks with a visuospatial component (2013, methodology): “Lexical Decision Test.”
The Overlap Model: A Model of Letter Position Coding (2008, unknown): “If the nonwords are wordlike, RT is slowed, and accuracy is reduced for word targets (e.g., Ratcliff et al., 2004).”
Diffusion Decision Model: Current Issues and History (2016, methodology): “Diffusion and other models have been applied to many basic perceptual and memory tasks such as item and associative recognition [2,15,121,122,132], lexical decision [121,133], perceptual tasks including brightness, letter, motion, visual search, contrast, orientation discrimination tasks [7,14,16,44”
Beyond mean response latency: Response time distributional analyses of semantic priming (2008, background): “…been work investigating how variables influence the underlying RT distributions in lexical decision and pronunciation performance (e.g., Andrews & Heathcote, 2001; Balota & Spieler, 1999; Plourde & Besner, 1997; Ratcliff et al., 2004; Yap & Balota, 2007; Yap, Balota, Cortese, & Watson, 2006).”
What cognitive processes drive response biases? A diffusion model analysis (2011, background): “Variability in the nondecision components, which was crucial to a successful diffusion model account of lexical decision data in Ratcliff, Gómez, and McKoon (2004), is included Judgment and Decision Making, Vol. 6, No. 7, October 2011 Diffusion model analysis of response biases 653 Figure 1:…”