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Found 179 results
Author [ Title(Asc)] Type Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z 
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Rosedahl, L. A., Serota R., & Ashby F. G. (2021).  When instructions don't help: Knowing the optimal strategy facilitates rule-based but not information-integration category learning. Journal of Experimental Psychology: Human Perception & Performance. 47, 1226-1236.
Alfonso-Reese, L. A., F Ashby G., & Brainard D. H. (2002).  What makes a categorization task difficult?. Attention, Perception, & Psychophysics. 64, 570–583.
Kovacs, P., & Ashby F. G. (2022).  On what it means to automatize a rule. Cognition. 226, 105168.
Roeder, J. L., & Ashby F. G. (2016).  What is automatized during perceptual categorization?. Cognition. 154, 22-33.
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F Ashby, G., & Townsend J. T. (1986).  Varieties of perceptual independence. Psychological Review. 93, 154-179.
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Ashby, F. G. (In Press).  On using the fixed-point property of binary mixtures to discriminate among models of recognition memory. Journal of Mathematical Psychology.
Ell, S. W., F Ashby G., & Hutchinson S. (2012).  Unsupervised category learning with integral-dimension stimuli. Quarterly Journal of Experimental Psychology. 65(8), 1537-1562.
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Crossley, M. J., Roeder J. L., Helie S., & Ashby F. G. (2018).  Trial-by-trial switching between procedural and declarative categorization systems. Psychological Research. 82, 371-384.
Helie, S., Turner B. O., Crossley M. J., Ell S. W., & Ashby F. G. (2017).  Trial-by-trial identification of categorization strategy using iterative decision-bound modeling. Behavioral Research Methods. 49(3), 1146-1162.
F Ashby, G., & Perrin N. A. (1988).  Toward a unified theory of similarity and recognition. Psychological Review. 95, 124-150.
J Smith, D., Zakrzewski A. C., Herberger E. R., Boomer J., Roeder J. L., F Ashby G., et al. (2015).  The time course of explicit and implicit categorization. Attention, Perception, & Psychophysics. 77(7), 2476-2490.
F Ashby, G., & Ennis D. M. (2002).  A Thurstone-Coombs model of concurrent ratings with sensory and liking dimensions. Journal of Sensory Studies. 17, 43–59.
F Ashby, G. (1982).  Testing the assumptions of exponential, additive reaction time models. Memory & Cognition. 10, 125–134.
Soto, F. A., Zheng E., Fonseca J., & Ashby F. G. (2017).  Testing separability and independence of perceptual dimensions with general recognition theory: A tutorial and new R package (grtools). Frontiers in Psychology. 8, 696.
Qadri, M. A. J., Ashby F. G., Smith J. D., & Cook R. G. (2019).  Testing analogical rule transfer in pigeons (Columba livia). Cognition. 183, 256-268.
Townsend, J. T., Hu G. G., & F Ashby G. (1980).  A test of visual feature sampling independence with orthogonal straight lines. Bulletin of the Psychonomic Society. 15, 163–166.
Perrin, N. A., & F Ashby G. (1991).  A test for perceptual independence with dissimilarity data. Applied Psychological Measurement. 15, 79–93.
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F Ashby, G., Waldron E. M., W Lee W., & Berkman A. (2001).  Suboptimality in human categorization and identification. Journal of Experimental Psychology: General. 130, 77.
Balakrishnanl, JD., & F Ashby G. (1992).  Subitizing: Magical numbers or mere superstition?. Psychological Research. 54, 80–90.
Balakrishnan, JD., & F Ashby G. (1991).  Is subitizing a unique numerical ability?. Perception & Psychophysics. 50, 555–564.
Ashby, F. G. (2000).  A stochastic version of general recognition theory. Journal of Mathematical Psychology. 44, 310–329.
Townsend, J. T., & F Ashby G. (1983).  Stochastic modeling of elementary psychological processes.
F Ashby, G. (1989).  Stochastic general recognition theory. Human information processing: Measures, mechanisms, and models. 435–457.
F Ashby, G., & W Maddox T. (1998).  Stimulus categorization. Measurement, judgment, and decision making. 251–301.
Ashby, F. G., & Wenger M. J. (2023).  Statistical decision theory. In F. G. Ashby, H. Colonius, & E. Dzhafarov (Eds.), The new handbook of mathematical psychology, Volume 3 (pp. 265-310). Cambridge University Press.

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