Robert M. Nosofsky

Indiana University, Bloomington, Bloomington, IN, United States 
categorization, mathematical psychology
"Robert Nosofsky"
Mean distance: 13.88 (cluster 15)
Cross-listing: PsychTree - MathTree

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Nosofsky RM, Cao R, Harding SM, et al. (2020) Modeling short- and long-term memory contributions to recent event recognition. Journal of Experimental Psychology. Learning, Memory, and Cognition
Nosofsky RM, Slaughter C, McDaniel MA. (2019) Learning hierarchically organized science categories: simultaneous instruction at the high and subtype levels. Cognitive Research: Principles and Implications. 4: 48
Miyatsu T, Nosofsky RM, McDaniel MA. (2019) Effects of specific-level versus broad-level training for broad-level category learning in a complex natural science domain. Journal of Experimental Psychology. Applied
Meagher BJ, Carvalho PF, Goldstone RL, et al. (2018) Correction to: Organized simultaneous displays facilitate learning of complex natural science categories. Psychonomic Bulletin & Review
Nosofsky RM, Sanders CA, Zhu X, et al. (2018) Model-guided search for optimal natural-science-category training exemplars: A work in progress. Psychonomic Bulletin & Review
Miyatsu T, Gouravajhala R, Nosofsky RM, et al. (2018) Feature highlighting enhances learning of a complex natural-science category. Journal of Experimental Psychology. Learning, Memory, and Cognition
Cao R, Shiffrin RM, Nosofsky RM. (2017) Item frequency in probe-recognition memory search: Converging evidence for a role of item-response learning. Memory & Cognition
Nosofsky RM, Sanders CA, McDaniel MA. (2017) Tests of an Exemplar-Memory Model of Classification Learning in a High-Dimensional Natural-Science Category Domain. Journal of Experimental Psychology. General
Nosofsky RM, Gold JM. (2017) Biased Guessing in a Complete-Identification Visual-Working-Memory Task: Further Evidence for Mixed-State Models. Journal of Experimental Psychology. Human Perception and Performance
Nosofsky RM, Sanders CA, Meagher BJ, et al. (2017) Toward the development of a feature-space representation for a complex natural category domain. Behavior Research Methods
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