Chris Donkin
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Benchmarks for models of short-term and working memory.
K Oberauer, S Lewandowsky, E Awh, GDA Brown, A Conway, N Cowan, ...
Psychological Bulletin 144 (9), 885, 2018
The hare and the tortoise: emphasizing speed can change the evidence used to make decisions
B Rae, A Heathcote, C Donkin, L Averell, S Brown
Journal of Experimental Psychology: Learning, Memory, and Cognition, 2014
Diffusion versus linear ballistic accumulation: different models but the same conclusions about psychological processes?
C Donkin, S Brown, A Heathcote, EJ Wagenmakers
Psychonomic bulletin & review 18 (1), 61-69, 2011
Short-term memory scanning viewed as exemplar-based categorization.
RM Nosofsky, DR Little, C Donkin, M Fific
Psychological review 118 (2), 280, 2011
Metastudies for robust tests of theory
B Baribault, C Donkin, DR Little, JS Trueblood, Z Oravecz, ...
Proceedings of the National Academy of Sciences 115 (11), 2607-2612, 2018
Is preregistration worthwhile?
A Szollosi, D Kellen, DJ Navarro, R Shiffrin, I van Rooij, T Van Zandt, ...
Trends in Cognitive Sciences, 2019
The overconstraint of response time models: Rethinking the scaling problem
C Donkin, SD Brown, A Heathcote
Psychonomic bulletin & review 16 (6), 1129-1135, 2009
The quality of response time data inference: A blinded, collaborative assessment of the validity of cognitive models
G Dutilh, J Annis, SD Brown, P Cassey, NJ Evans, RPPP Grasman, ...
Psychonomic Bulletin & Review 26 (4), 1051-1069, 2019
Discrete-slots models of visual working-memory response times.
C Donkin, RM Nosofsky, JM Gold, RM Shiffrin
Psychological Review, 2013
An integrated model of choices and response times in absolute identification.
SD Brown, AAJ Marley, C Donkin, A Heathcote
Psychological Review 115 (2), 396, 2008
A power-law model of psychological memory strength in short-and long-term recognition
C Donkin, RM Nosofsky
Psychological science 23 (6), 625-634, 2012
The EZ diffusion model provides a powerful test of simple empirical effects
D van Ravenzwaaij, C Donkin, J Vandekerckhove
Psychonomic bulletin & review 24 (2), 547-556, 2017
Measuring Intuition: Nonconscious Emotional Information Boosts Decision Accuracy and Confidence
G Lufityanto, C Donkin, J Pearson
Psychological Science 1, 13, 2016
Drawing conclusions from choice response time models: A tutorial using the linear ballistic accumulator
C Donkin, S Brown, A Heathcote
Journal of Mathematical Psychology 55 (2), 140-151, 2011
Robust modeling in cognitive science
MD Lee, AH Criss, B Devezer, C Donkin, A Etz, FP Leite, D Matzke, ...
Computational Brain & Behavior, 1-13, 2019
Unconscious information changes decision accuracy but not confidence
A Vlassova, C Donkin, J Pearson
Proceedings of the National Academy of Sciences 111 (45), 16214-16218, 2014
Cognitive control and counterproductive oculomotor capture by reward-related stimuli
D Pearson, C Donkin, SC Tran, SB Most, ME Le Pelley
Visual Cognition, 2015
Getting more from accuracy and response time data: Methods for fitting the linear ballistic accumulator
C Donkin, L Averell, S Brown, A Heathcote
Behavior research methods 41 (4), 1095-1110, 2009
Converging measures of workload capacity
A Eidels, C Donkin, SD Brown, A Heathcote
Psychonomic bulletin & review 17 (6), 763-771, 2010
Arrested theory development: The misguided distinction between exploratory and confirmatory research
A Szollosi, C Donkin
Perspectives on Psychological Science 16 (4), 717-724, 2021
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Artikelen 1–20