John K. Kruschke

Q: What Schools Are Affiliated With John K. Kruschke

John K. Kruschke is affiliated with the following schools: University of California, Berkeley, Indiana University Bloomington, Indiana University, University of California, Davis

John K. Kruschke's AcademicInfluence.com Rankings

John K. Kruschke

Psychology

#1605

World Rank

#1927

Historical Rank

Cognitive Psychology

#187

World Rank

#193

Historical Rank

psychology Degrees

Download Badge

Psychology

Why Is John K. Kruschke Influential?

(Suggest an Edit or Addition)

According to Wikipedia, John Kendall Kruschke is an American psychologist and statistician known for his work in connectionist models of human learning, and in Bayesian statistical analysis. He is Provost Professor Emeritus in the Department of Psychological and Brain Sciences at Indiana University Bloomington. He won the Troland Research Award from the National Academy of Sciences in 2002.

(See a Problem?)

John K. Kruschke's Published Works

Number of citations in a given year to any of this author's works

Total number of citations to an author for the works they published in a given year. This highlights publication of the most important work(s) by the author

Published Works

Bayesian data analysis. (2010) (8811)
ALCOVE: an exemplar-based connectionist model of category learning. (1992) (1676)
Doing Bayesian Data Analysis: A Tutorial with R, JAGS, and Stan (2014) (1323)
Bayesian estimation supersedes the t test. (2013) (1231)
Doing Bayesian Data Analysis: A Tutorial with R and BUGS (2010) (638)
Rules and exemplars in category learning. (1998) (601)
The Bayesian New Statistics: Hypothesis testing, estimation, meta-analysis, and power analysis from a Bayesian perspective (2016) (588)
The Time Has Come (2012) (385)
Bayesian Assessment of Null Values Via Parameter Estimation and Model Comparison (2011) (378)
Doing Bayesian Data Analysis (2010) (354)
Toward a unified model of attention in associative learning (2001) (322)
Analyzing Ordinal Data with Metric Models: What Could Possibly Go Wrong? (2017) (306)
Rejecting or Accepting Parameter Values in Bayesian Estimation (2018) (294)
What to believe: Bayesian methods for data analysis (2010) (288)
A model of probabilistic category learning. (1999) (265)
Bayesian data analysis for newcomers (2018) (242)
Combining exemplar-based category representations and connectionist learning rules. (1992) (215)
Blocking and backward blocking involve learned inattention (2000) (202)
Base rates in category learning. (1996) (188)
Attention in Learning (2003) (180)
Human Category Learning: Implications for Backpropagation Models (1993) (179)
Eye gaze and individual differences consistent with learned attention in associative blocking and highlighting. (2005) (163)
Benefits of gain: speeded learning and minimal hidden layers in back-propagation networks (1991) (144)
Bayesian approaches to associative learning: From passive to active learning (2008) (140)
Decision-making in stimulant and opiate addicts in protracted abstinence: evidence from computational modeling with pure users (2014) (133)
Dimensional Relevance Shifts in Category Learning (1996) (129)
Population of linear experts: knowledge partitioning and function learning. (2004) (122)
Locally Bayesian learning with applications to retrospective revaluation and highlighting. (2006) (110)
Bayesian learning theory applied to human cognition. (2011) (106)
Editorial: Bayesian methods for advancing psychological science (2018) (100)
Chapter 8 – JAGS (2015) (92)
Bayesian estimation in hierarchical models (2015) (86)
Attentional processes in stereotype formation: a common model for category accentuation and illusory correlation. (2009) (80)
The inverse base-rate effect is not explained by eliminative inference. (2001) (72)
Rule-based extrapolation in perceptual categorization (2002) (70)
Investigations of an Exemplar-Based Connectionist Model of Category Learning (1992) (61)
Category representation for classification and feature inference. (2005) (59)
Single-system models and interference in category learning: Commentary on Waldron and Ashby (2001) (2002) (54)
Learning Involves Attention (2000) (52)
Introduction to Special Section on Bayesian Data Analysis (2011) (51)
The Bayesian New Statistics: Hypothesis testing, estimation, meta-analysis, and power analysis from a Bayesian perspective (2017) (51)
The Cambridge Handbook of Computational Psychology: Models of Categorization (2008) (50)
Bayesian Analysis Reporting Guidelines (2021) (47)
Models of Attentional Learning (2011) (47)
Sequential Learning Models for the Wisconsin Card Sort Task: Assessing Processes in Substance Dependent Individuals. (2010) (46)
The perception of causality: Feature binding in interacting objects (1996) (46)
Using cognitive science methods to assess the role of social information processing in sexually coercive behavior. (2001) (46)
Posterior predictive checks can and should be Bayesian: comment on Gelman and Shalizi, 'Philosophy and the practice of Bayesian statistics'. (2013) (46)
Attention and salience in associative blocking (2006) (41)
Three principles for models of category learning (1993) (39)
Assessing clinically relevant perceptual organization with multidimensional scaling techniques. (2002) (37)
Integrating advice and experience: learning and decision making with social and nonsocial cues. (2011) (36)
Associative learning in baboons (Papio papio) and humans (Homo sapiens): species differences in learned attention to visual features (1998) (36)
The Bayesian New Statistics: Two historical trends converge (2015) (32)
Highlighting : A Canonical Experiment (2009) (31)
Decision boundaries in one-dimensional categorization. (1997) (29)
Improving generalization in backpropagation networks with distributed bottlenecks (1989) (27)
The role of attention shifts in the categorization of continuous dimensioned stimuli (2000) (26)
Ostracism and fines in a public goods game with accidental contributions: The importance of punishment type (2014) (25)
Attentional Theory Is a Viable Explanation of the Inverse Base Rate Effect: A Reply to Winman, Wennerholm, and Juslin (2003) (2003) (25)
Dissociating stimulus-set and response-set in the context of task-set switching. (2013) (25)
Shifting attention in cued recall (1998) (23)
Tutorial: Doing Bayesian Data Analysis with R and BUGS (2011) (21)
Chapter 5 Highlighting (2009) (21)
Learned Attention (2006) (15)
Rule-based extrapolation: A continuing challenge for exemplar models (2008) (15)
Contextual modulation of attention in human category learning (2012) (14)
Locally Bayesian Learning (2006) (13)
Men's memory for women's sexual-interest and rejection cues (2011) (13)
Lay evaluations of police and civilian use of force: Action severity scales. (2019) (13)
Learning of rules that have high-frequency exceptions: New empirical data and a hybrid connectionist model (2019) (12)
ALCOVE: A Connectionist Model of Human Category Learning (1990) (12)
Clinical Cognitive Science: Applying Quantitative Models of Cognitive Processing to Examine Cognitive Aspects of Psychopathology. (2007) (11)
Doing Bayesian Data Analysis: Blog Backup (2017) (11)
Role of attention, memory, and covariation-detection processes in clinically significant eating-disorder symptoms (2010) (10)
Cue competition in function learning: Blocking and highlighting (2001) (10)
Computational Models of Conditioning: Evolution of attention in learning (2010) (10)
Mathematical Learning Theory (2001) (9)
Distributed bottlenecks for improved generalization in back-propagation networks (1989) (9)
An Evolutionary Analysis of Learned Attention (2015) (7)
Bridging levels of analysis: comment on McClelland et al. and Griffiths et al. (2010) (6)
Analyzing Ordinal Data: Support for a Bayesian Approach (2015) (6)
Are rules and instances subserved by separate systems? (1994) (6)
Chapter 7 – Markov Chain Monte Carlo (2015) (6)
Multiple Representations in Inductive Category Learning: Evidence of Stimulus- and Time-Dependent Re (2001) (6)
Chapter 2 – Introduction: Credibility, Models, and Parameters (2015) (5)
Cross-language similarity and difference in quantity categorization of Finnish and Japanese (2015) (5)
Chapter 9 – Hierarchical Models (2015) (5)
Chapter 5 – Bayes' Rule (2015) (5)
Tutorial: Bayesian data analysis (2015) (4)
Extensions to the delta rule for associative learning (1995) (4)
How connectionist models learn: The course of learning in connectionist networks (1990) (3)
Chapter 12 – Bayesian Approaches to Testing a Point (“Null”) Hypothesis (2015) (3)
Chapter 4 – What is This Stuff Called Probability? (2015) (3)
Backward blocking of relevance-indicating cues: Evidence for locally Bayesian learning (2010) (3)
Chapter 1 – What's in This Book (Read This First!) (2015) (3)
Chapter 13 – Goals, Power, and Sample Size (2015) (3)
Categorization and Similarity Models (2001) (3)
Chapter 3 – The R Programming Language (2015) (3)
The Bayesian New Statistics (Public) (2016) (3)
Singles of both sexes expedite reproduction: Shifts in sexual-timing strategies before and after the typical age of female menopause (2019) (3)
Moral Foundation Sensitivity and Perceived Humor (2014) (3)
Chapter 11 – Null Hypothesis Significance Testing (2015) (3)
Chapter 25 – Tools in the Trunk (2015) (3)
Exemplar Model Account of Inference Learning (1999) (3)
Associative learning in baboons and humans: Species differences in learned attention to visual features (1998) (2)
Chapter 18 – Metric Predicted Variable with Multiple Metric Predictors (2015) (2)
Chapter 20 – Metric Predicted Variable with Multiple Nominal Predictors (2015) (2)
An Interactive Classroom Demonstration of Propositional and Analogical Representation (1996) (2)
Chapter 6 – Inferring a Binomial Probability via Exact Mathematical Analysis (2015) (2)
Chapter 17 – Metric Predicted Variable with One Metric Predictor (2015) (2)
Illusory Correlation and the Inverse Base Rate Effect: Different Underlying Mechanisms (2006) (2)
Serial reproduction of narratives preserves emotional appraisals (2022) (2)
Chapter 23 – Ordinal Predicted Variable (2015) (2)
Application of Associative Learning Paradigms to Clinically Relevant Individual Differences in Cognitive Processing (2011) (2)
A Cue Imputation Bayesian Model of Information Aggregation (2011) (2)
Chapter 19 – Metric Predicted Variable with One Nominal Predictor (2015) (2)
Editorial: Bayesian methods for advancing psychological science (2018) (1)
Lay evaluations of police and civilian use of force: Appropriate police reactions are less severe than civilian resistance (2018) (1)
Concept Learning and Categorization: Models (2006) (1)
Rule and Exemplar Representation in Rule-defined Category Structures (1999) (1)
Ordinal Data Analysis (2017) (1)
Chapter 10 – Model Comparison and Hierarchical Modeling (2015) (1)
Uncertainty of prior and posterior model probability: Implications for interpreting Bayes factors (1)
Chapter 16 – Metric-Predicted Variable on One or Two Groups (2015) (1)
Chapter 14 – Stan (2015) (1)
P457/P654 Readings in the Science of Morality (2011) (0)
Eye Tracking, Individual Differences, and Attention in Associative Learning (2006) (0)
Further Reading Statistical Methods: Overview the Purpose of Inferential Statistics Examples of the Need for Inferential Statistics (0)
Bayesian data analysis for newcomers (2017) (0)
Chapter 15 – Overview of the Generalized Linear Model (2015) (0)
Singles of Both Sexes Expedite Reproduction (2019) (0)
Lay evaluations of police and civilian use of force: Moral and physical magnitude ratings of officer and civilian actions (2018) (0)
Multiple comparisons and power make sense in Bayesian analysis: (520592012-037) (2010) (0)
State transitions in constraint satisfaction networks (1989) (0)
Chapter 22 – Nominal Predicted Variable (2015) (0)
What Representation Results from Feature Inference Category Learning (2003) (0)
Running head : SEQUENTIAL LEARNING MODELS 2 3 4 Sequential Learning Models for the Wisconsin Card Sort Task : Assessing Processes in 5 Substance Dependent Individuals 6 7 (2010) (0)
Lay evaluations of police and civilian use of force: Action severity scales (2018) (0)
The Disappearance of Moral Choice in Serially Reproduced Narratives (2013) (0)
Emotional Valence of Narratives Is Preserved Across Multiple Retellings (2020) (0)
Attentional Perseveration after the Inverse Base--Rate Effect (2000) (0)
The Role of Base Rates in Category Learning (1996) (0)
Contextual modulation of attention in human category learning (2012) (0)
Selective Attention in Associative Learning. Review ofThe Psychology of Associative Learning,by D. R. Shanks (1997) (0)
Statistical Methods: Overview (2006) (0)
Chapter 21 – Dichotomous Predicted Variable (2015) (0)
Category Learning 1 Running head: CATEGORY LEARNING; KRUSCHKE Category Learning (chapter for volume edited by Lamberts and Goldstone) (2003) (0)
HIGHLIGHTING: A NEW (2003) (0)
Chapter 24 – Count Predicted Variable (2015) (0)
Categorization and Similarity Models: Neuroscience Applications (0)
ALCOVE: An exemplar-based connectionist model of category learning (2020) (0)
Application of Associative Learning Paradigms to (2009) (0)

This paper list is powered by the following services:

Other Resources About John K. Kruschke

What Schools Are Affiliated With John K. Kruschke?

John K. Kruschke is affiliated with the following schools: