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John K. Kruschke
John K. Kruschke
Provost Professor Emeritus, Indiana University
Verified email at iu.edu - Homepage
Title
Cited by
Cited by
Year
Doing Bayesian Data Analysis, Second Edition: A Tutorial with R, JAGS, and Stan
JK Kruschke
Academic Press, 2015
4888*2015
ALCOVE: An exemplar-based connectionist model of category learning.
JK Kruschke
Psychological review 99 (1), 22, 1992
2537*1992
Bayesian estimation supersedes the t test.
JK Kruschke
Journal of Experimental Psychology: General 142 (2), 573-603, 2013
17412013
The Bayesian new statistics: Hypothesis testing, estimation, meta-analysis, and power analysis from a Bayesian perspective
JK Kruschke, TM Liddell
Psychonomic Bulletin & Review, 2016
12222016
Rules and exemplars in category learning.
MA Erickson, JK Kruschke
Journal of Experimental Psychology: General 127 (2), 107, 1998
8941998
Analyzing ordinal data with metric models: What could possibly go wrong?
TM Liddell, JK Kruschke
Journal of Experimental Social Psychology 79, 328-348, 2018
6532018
Rejecting or Accepting Parameter Values in Bayesian Estimation
JK Kruschke
Advances in Methods and Practices in Psychological Science, 2018
592*2018
Bayesian assessment of null values via parameter estimation and model comparison
JK Kruschke
Perspectives on Psychological Science 6 (3), 299, 2011
5342011
The time has come: Bayesian methods for data analysis in the organizational sciences
JK Kruschke, H Aguinis, H Joo
Organizational Research Methods 15 (4), 722-752, 2012
5202012
Bayesian data analysis for newcomers
JK Kruschke, TM Liddell
Psychonomic bulletin & review 25 (1), 155-177, 2018
4482018
Toward a unified model of attention in associative learning
JK Kruschke
Journal of mathematical psychology 45 (6), 812-863, 2001
4322001
Combining exemplar-based category representations and connectionist learning rules.
RM Nosofsky, JK Kruschke, SC McKinley
Journal of Experimental Psychology: Learning, Memory, and Cognition 18 (2), 211, 1992
4301992
What to believe: Bayesian methods for data analysis
JK Kruschke
Trends in cognitive sciences 14 (7), 293-300, 2010
4142010
A model of probabilistic category learning.
JK Kruschke, MK Johansen
Journal of Experimental Psychology: Learning, Memory, and Cognition 25 (5), 1083, 1999
3491999
Bayesian data analysis
JK Kruschke
Wiley Interdisciplinary Reviews: Cognitive Science 1 (5), 658-676, 2010
3212010
Blocking and backward blocking involve learned inattention
JK Kruschke, NJ Blair
Psychonomic Bulletin & Review 7 (4), 636-645, 2000
2972000
Base rates in category learning.
JK Kruschke
Journal of Experimental Psychology: Learning, Memory, and Cognition 22 (1), 3, 1996
2731996
Attention in learning
JK Kruschke
Current Directions in Psychological Science 12 (5), 171-175, 2003
2532003
Eye gaze and individual differences consistent with learned attention in associative blocking and highlighting.
JK Kruschke, ES Kappenman, WP Hetrick
Journal of Experimental Psychology: Learning, Memory, and Cognition 31 (5), 830, 2005
2412005
Benefits of gain: Speeded learning and minimal hidden layers in back-propagation networks
JK Kruschke, JR Movellan
IEEE Transactions on systems, Man, and Cybernetics 21 (1), 273-280, 1991
2221991
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