Publications

Submitted Manuscripts

  1. Bartlema, A., Lee, M.D., Wetzels, R., & Vanpaemel, W. (submitted). Bayesian hierarchical mixture models of individual differences in selective attention and representation in category learning. [pdf]
  2. Zhang, S., Lee. M.D., Vandekerckhove, J., Maris, G., and Wagenmakers, E.-J. (submitted). On the relationship between diffusion and accumulator sequential sampling models. [pdf]
  3. van Ravenzwaaij, D., Moore, C.P, Lee, M.D., & Newell, B,R, (submitted). Is take the best for the best? A hierarchical Bayesian modeling approach to searching and stopping. [pdf]

Books

  1. Lee, M.D., & Wagenmakers, E.-J. (forthcoming). Bayesian cognitive modeling: A practical course. Cambridge University Press. [Amazon link US] [Amazon link UK]

Journal Articles

  1. Lee, M.D. (1997). The connectionist construction of psychological spaces. Connection Science, 9, 323-351.
  2. Lee, M.D., Vickers, D., & Brown, M. (1997). Neural network and tree search algorithms for the generation of path-following (trail making) tests. Journal of Intelligent Systems, 7, 117-143.
  3. Vickers, D., & Lee, M.D. (1997). Towards a dynamic connectionist model of memory. Behavioral and Brain Sciences, 20, 40-41.
  4. Lee, M.D. (1998). Neural feature abstraction from judgments of similarity. Neural Computation, 10, 1815-1830.
  5. Vickers, D., & Lee, M.D. (1998). Dynamic models of simple judgments: I. Properties of a self-regulating accumulator module. Non-linear Dynamics, Psychology, and Life Sciences, 2, 169-194. [pdf]
  6. Vickers, D., & Lee, M.D. (1998). Never cross the path of a traveling salesman: The neural network generation of Halstead-Reitan trail making tests. Behavior Research, Methods, Instruments, & Computers, 30 423-431.
  7. Lee, M.D. (1999). An extraction and regularization approach to additive clustering. Journal of Classification, 16, 255-281.
  8. Lee, M.D., & Vickers, D. (2000). The importance of the convex hull for human performance on the traveling salesman problem: Comment on Macgregor & Ormerod (1996). Perception & Psychophysics, 62, 226-228.
  9. Vickers, D., & Lee, M.D. (2000). Dynamic models of simple judgments: II. Properties of a Parallel, Adaptive, Generalised Accumulator Network (PAGAN) model for multi-choice tasks. Non-linear Dynamics, Psychology, and Life Sciences, 4, 1-31. [pdf]
  10. Lee, M.D. (2001). On the complexity of additive clustering models. Journal of Mathematical Psychology, 45, 131-148. [pdf]
  11. Lee, M.D. (2001). Determining the dimensionality of multidimensional scaling models for cognitive modeling. Journal of Mathematical Psychology, 45, 149-166. [pdf]
  12. Lee, M.D. (2001). Extending Bayesian concept learning to deal with representational complexity and adaptation. Behavioral and Brain Sciences, 24, 685-686. [pdf]
  13. Vickers, D., Butavicius, M.A., Lee, M.D., & Medvedev, A. (2001). Human performance on visually presented traveling salesman problems. Psychological Research, 65, 34-45.
  14. Lee, M.D. (2002). A simple method for generating additive clustering models with limited complexity. Machine Learning, 49, 39-58. [pdf]
  15. Lee, M.D. (2002). Generating additive clustering models with limited stochastic complexity. Journal of Classification, 19, 69-85. [pdf]
  16. Lee, M.D., Loughlin, N., & Lundberg, I.B. (2002). Applying one reason decision making: The prioritization of literature searches. Australian Journal of Psychology, 54, 137-143. [pdf]
  17. Lee, M.D., & Navarro, D.J. (2002). Extending the ALCOVE model of category learning to featural stimulus domains. Psychonomic Bulletin & Review, 9, 43-58. [pdf]
  18. Lee, M.D., & Corlett, E.Y. (2003). Sequential sampling models of human text classification. Cognitive Science, 27, 159-193. [pdf]
  19. Lee, M.D., & Pope, K.J. (2003). Avoiding the dangers of averaging across subjects when using multidimensional scaling. Journal of Mathematical Psychology, 47, 32-46. [pdf]
  20. Lee, M.D., Butavicius, M.A., & Reilly, R.E. (2003). Visualizations of binary data: A comparative evaluation. International Journal of Human-Computer Studies, 59, 569-602. [pdf]
  21. Vickers, D., Bovet, P., Lee, M.D., & Hughes, P. (2003). The perception of minimal structures: Performance on open and closed versions of visually presented Euclidean Traveling Salesperson problems. Perception, 32, 871-886. [pdf]
  22. Vickers, D., Lee, M.D., Dry, M., & Hughes, P. (2003). The roles of the convex hull and number of intersections upon performance on visually presented traveling salesperson problems. Memory & Cognition, 31, 1094-1104. [pdf]
  23. Vickers, D., Mayo, T., Heitman, M., Lee, M.D., & Hughes, P. (2004). Intelligence and individual differences in performance on three types of visually presented optimisation problems. Personality and Individual Differences, 36, 1059-1071. [pdf]
  24. Lee, M.D., & Cummins, T.D.R. (2004). Evidence accumulation in decision making: Unifying the ‘take the best’ and ‘rational’ models. Psychonomic Bulletin & Review, 11, 343-352. [pdf]
  25. Lee, M.D. (2004). A Bayesian analysis of retention functions. Journal of Mathematical Psychology, 48, 310-321. [pdf]
  26. Navarro, D.J., & Lee, M.D. (2004). Common and distinctive features in stimulus representation: A modified version of the contrast model. Psychonomic Bulletin & Review, 11, 961–974. [pdf]
  27. Lee, M.D., & Wagenmakers, E.-J. (2005). Bayesian statistical inference in psychology: Comment on Trafimow (2003). Psychological Review, 112, 662-668. [pdf]
  28. Mackay, M., & Lee, M.D., (2005). Choice of models for the analysis and forecasting of hospital beds. Health Care Management Science Journal, 8, 221-230.
  29. Lee, M.D., & Webb, M.R. (2005). Modeling individual differences in cognition. Psychonomic Bulletin & Review, 12, 605-621. [pdf]
  30. Vickers, D., Lee, M.D., Dry, M., Hughes, P., & McMahon, J.A. (2006). The aesthetic appeal of minimal structures: Judging the attractiveness of solutions to Traveling Salesperson problems. Perception & Psychophysics, 68, 32-42. [pdf]
  31. Navarro, D.J., Griffiths, T.L., Steyvers, M., & Lee, M.D. (2006). Modeling individual differences with Dirichlet processes. Journal of Mathematical Psychology, 50, 101-102. [pdf]
  32. Lee, M.D., & Pope, K.J. (2006). Model selection for the rate problem: A comparison of significance testing, Bayesian, and minimum description length statistical inference.  Journal of Mathematical Psychology, 50, 193-202. [pdf]
  33. Lee, M.D. (2006). A hierarchical Bayesian model of human decision-making on an optimal stopping problem. Cognitive Science, 30, 555-580.  [pdf]
  34. Burns, N.R., Lee, M.D., & Vickers, D. (2006). Are individual differences in performance on perceptual and cognitive optimization problems determined by general intelligence? Journal of Problem Solving, 1, 5-19. [pdf]
  35. Dry, M.J., Lee, M.D., Vickers, D., & Hughes, P. (2006). Human performance on visually presented traveling salesperson problems with varying numbers of nodes. Journal of Problem Solving, 1, 20-32. [pdf]
  36. Lee, M.D., & Dry, M.J. (2006). Decision-making and confidence given uncertain advice. Cognitive Science. 30, 1081-1095. [pdf]
  37. Butavicius, M.A., & Lee, M.D. (2007). An empirical evaluation of four data visualization techniques for displaying short news text similarities. International Journal of Human-Computer Studies, 65, 931-944. [pdf]
  38. Malhotra, V., Lee, M.D., & Khurana, A.K. (2007). Domain experts influence decision quality: Towards a robust method for their identification. Journal of Petroleum Science and Engineering, 57, 181-194. [pdf]
  39. Lee, M.D., & Paradowski, M.J. (2007). Group performance on an optimal stopping problem. Journal of Problem Solving, 1, 53-73. [pdf] (Accompanying technical note [pdf]).
  40. Lee, M.D. (2008). Three case studies in the Bayesian analysis of cognitive models. Psychonomic Bulletin & Review, 15, 1-15. [pdf]
  41. Fletcher, K.I., Butavicius, M.A., & Lee, M.D. (2008).  Attention to internal features in unfamiliar face matching. British Journal of Psychology, 99, 379-394. [pdf]
  42. Lee, M.D. (2008). BayesSDT: Software for Bayesian inference with signal detection theory. Behavior Research Methods, 40, 450-456. [pdf]
  43. Lee, M.D., & Vanpaemel, W. (2008). Exemplars, prototypes, similarities and rules in category representation: An example of hierarchical Bayesian analysis. Cognitive Science, 32, 1403-1424. [pdf]
  44. Chronicle, E.P., MacGregor, J.N., Lee, M.D., Ormerod, T.C., & Hughes, P. (2008). Individual differences in optimization problem solving: Reconciling conflicting results. Journal of Problem Solving, 2, 41-49. [pdf]
  45. Dennis, S.J., Lee, M.D., & Kinnell, A. (2008). Bayesian analysis of recognition memory: The case of the list-length effect. Journal of Memory & Language, 59, 361-376. [pdf]
  46. Shiffrin, R.M., Lee, M.D., Wagenmakers, E.-J., & Kim, W.J. (2008). A survey of model evaluation approaches with a focus on hierarchical Bayesian methods. Cognitive Science, 32, 1248-1284. [pdf]
  47. Iverson, G.J., Lee, M.D., & Wagenmakers, E.-J. (2009). prep misestimates the probability of replication. Psychonomic Bulletin & Review, 16, 424-429. [pdf]
  48. Steyvers, M., Lee, M.D., & Wagenmakers, E.-J. (2009). A Bayesian analysis of human decision-making on bandit problems. Journal of Mathematical Psychology, 53, 168-179. [pdf]‘
  49. Iverson, G.J., Lee, M.D., Zhang, S., & Wagenmakers, E.-J. (2009). prep: An agony in five fits. Journal of Mathematical Psychology, 53, 195-202. [pdf]
  50. Sarnecka, B.W., & Lee, M.D. (2009). Levels of number knowledge in early childhood. Journal of Experimental Child Psychology, 103, 325-337. [pdf]
  51. Yi, S.K.M., Steyvers, M., & Lee, M.D. (2009). Modeling human performance in restless bandits using particle filters. Journal of Problem Solving, 2, 33-53. [pdf]
  52. Lee, M.D., & Sarnecka, B.W. (2010). A model of knower-level behavior in number-concept development. Cognitive Science, 34, 51-67. [pdf]
  53. Zeigenfuse, M.D., & Lee, M.D. (2010). Finding the features that represent stimuli. Acta Psychologica, 133, 283-295. [pdf]
  54. Iverson, G.J., Wagenmakers, E.-J., & Lee, M. D. (2010). A model averaging approach to replication: The case of prep. Psychological Methods, 15, 172-181. [pdf]
  55. Iverson, G.J, Lee, M.D., & Wagenmakers, E.-J. (2010). The random-effects prep continues to mispredict the probability of replication. Psychonomic Bulletin & Review, 17, 270-272. [pdf] Accompanying technical note [pdf]
  56. Wetzels, R., Lee, M.D., & Wagenmakers, E.-J. (2010). Bayesian inference using WBDev: A tutorial for social scientists. Behavior Research Methods, 42, 884-897. [pdf]
  57. Macguire, A.M., Humphreys, M.S., Dennis, S.J., & Lee, M.D. (2010). Global similarity accounts of embedded-category designs: Test of the global matching models. Journal of Memory & Language, 63, 131-148. [pdf]
  58. Zeigenfuse, M.D., & Lee, M.D. (2010). A general latent-assignment approach for modeling psychological contaminants. Journal of Mathematical Psychology, 54, 352-362. [pdf]
  59. Lee, M.D. (2010). Emergent and structured cognition in Bayesian models: Comment on Griffiths et al and McClelland et al. Trends in Cognitive Sciences, 14, 345-346. [pdf]
  60. Zhang, S., & Lee, M.D. (2010). Optimal experimental design for a class of bandit problems. Journal of Mathematical Psychology, 54, 499-508. [pdf]
  61. Vandekerckhove, J., Tuerlinckx, F., & Lee, M.D. (2011). Hierarchical diffusion models for two-choice response time. Psychological Methods, 16, 44-62. [pdf]
  62. Lee, M.D., Zhang, S., Munro, M.N., & Steyvers, M. (2011). Psychological models of human and optimal performance on bandit problems. Cognitive Systems Research, 12, 164-174. [pdf]
  63. Lee, M.D. (2011).  How cognitive modeling can benefit from hierarchical Bayesian models. Journal of Mathematical Psychology, 55, 1-7. [pdf]
  64. Pooley. J.P., Lee, M.D., & Shankle. W.R. (2011). Understanding Alzheimer’s using memory models and hierarchical Bayesian analysis. Journal of Mathematical Psychology, 55, 47-56. [pdf]
  65. Lee, M.D., Zhang, S., & Shi, J. (2011). The wisdom of the crowd playing the Price is Right. Memory & Cognition, 39, 914-923. [pdf] [accompanying technical note]
  66. Lee, M.D., & Sarnecka, B.W. (2011). Number knower-levels in young children: Insights from a Bayesian model. Cognition, 120, 391-402. [pdf] [supplementary note]
  67. Wetzels, R., Matzke, D., Lee, M.D., Rouder, J.N., Iverson, G.J., & Wagenmakers, E.-J. (2011). Statistical evidence in experimental psychology: An empirical comparison using 855 t-tests. Perspectives in Psychological Science, 6, 291-298. [pdf]
  68. Lee, M.D. (2011). In praise of ecumenical Bayes. Behavioral and Brain Sciences, 34, 206-207. [pdf]
  69. Newell, B.R., & Lee, M.D. (2011).  The right tool for the job? Comparing an evidence accumulation and a naive strategy selection model of decision making. Journal of Behavioral Decision Making, 24, 456-481. [pdf]
  70. Lodewyckx, T., Kim, W.-J., Lee, M.D., Tuerlinckx, F., Kuppens, P., & Wagenmakers, E.-J. (2011). A tutorial on Bayes Factor estimation with the product space method. Journal of Mathematical Psychology, 55, 331-347. [pdf]
  71. Navarro, D.J., Dry, M.J., & Lee, M.D. (2012). Sampling assumptions in inductive generalization. Cognitive Science, 36, 187-223. [pdf]
  72. Yi, S.K., Steyvers, M., Lee, M.D, & Dry, M.D. (2012). The wisdom of the crowd in combinatorial problems. Cognitive Science, 36,452-470. [pdf]
  73. Negen, J., Sarnecka, B.W., & Lee, M.D. (2012). An Excel sheet for inferring children’s number-knower-levels from Give-N data. Behavior Research Methods, 44, 57-66. [pdf]
  74. Lee, M.D., & Newell, B.R. (2011). Using hierarchical Bayesian methods to examine the tools of decision-making. Judgment and Decision Making, 6, 832-842. [pdf] [code]
  75. Lee, M.D., Steyvers, M., de Young, M., & Miller. B.J. (2012). Inferring expertise in knowledge and prediction ranking tasks. Topics in Cognitive Science, 4, 151-163. [pdf]
  76. Butavicius, M.A., Lee, M.D., Pincombe, B.M., Mullen, L.G., Navarro, D.J., Parsons, K.M., & McCormac, A. (2012). An assessment of email and spontaneous dialogue visualizations. International Journal of Human-Computer Studies, 70, 432-439. [pdf]
  77. Shankle, W.R., Pooley, J.P., Steyvers, M., Hara. J., Mangrola, T., Reisberg, B., & Lee, M.D. (2013). Relating memory to functional capacity in normal aging to dementia using hierarchical Bayesian cognitive processing models. Alzheimer Disease & Associated Disorders, 27, 16-22. [pdf]
  78. Shankle, W.R., Hara, J., Mangrola, T., Hendrix, S., Alva, G., & Lee, M.D. (in press). Hierarchical Bayesian cognitive processing models to analyze clinical trial data. Alzheimer’s & Dementia. Accepted 3-Feb-2012. [pdf]
  79. Ortega, A., Wagenmakers, E.-J., Lee, M.D., Markowitsch, H.J., & Piefke, M. (2012). A Bayesian latent group analysis for detecting poor effort in the assessment of malingering. Archives of Clinical Neuropsychology, 27, 453-465. [pdf]
  80. Vanpaemel, W., & Lee, M.D. 2012). The Bayesian evaluation of categorization models: Comment on Wills and Pothos (2012). Psychological Bulletin, 138, 1253-1258. [pdf]
  81. Lee, M.D., & Zhang, S. (2012). Evaluating the process coherence of take-the-best in structured environments. Judgment and Decision Making, 7, 360-372. [link]
  82. Vanpaemel, W., & Lee, M.D. (2012). Using priors to formalize theory: Optimal attention and the Generalized Context Model. Psychonomic Bulletin & Review, 19, 1047-1056. [pdf]
  83. Lee, M.D., & Pooley. J.P. (2013). Correcting the SIMPLE model of free recall. Psychological Review, 120, 293-296. [pdf]
  84. Lee, M.D., & Vanpaemel, W. (in press). Quantum models of cognition as Orwellian newspeak. Behavioral and Brain Sciences. [pdf]

Refereed Conference Papers

  1. Lee, M.D. (1996). A neural network which [sic] learns psychological internal representations. Proceedings of the 1996 Australian New-Zealand Conference on Intelligent Information Systems, 182-185.
  2. Lee, M.D. (1998). Interactive visualisation of similarity structures. In P. Calder and B.H. Thomas (Eds.), Proceedings of OZCHI 98, pp. 292-299. Piscataway, NJ: IEEE.
  3. Vickers, D., Navarro, D.J., & Lee, M.D. (2000). Towards a transformational approach to perceptual organization. In: R.J. Howlett & L.C. Jain (Eds.), KES 2000: Proceedings of the Fourth International Conference on Knowledge-Based Intelligent Engineering Systems & Allied Technologies, Vol. 1, pp. 325-328. Piscataway, NJ: IEEE.
  4. Lee, M.D. (2001). Fast text classification using sequential sampling processes. In M. Stumptner, D. Corbett, and M. Brooks (Eds.), AI 2001: Advances in Artificial Intelligence, Springer-Verlag Lecture Notes on Artificial Intelligence, 2256, pp. 309-320. Berlin: Springer-Verlag. [pdf]
  5. Navarro, D.J., & Lee, M.D. (2001). Clustering using the contrast model. In J.D. Moore & K. Stenning, (Eds.), Proceedings of the 23rd Annual Conference of the Cognitive Science Society, pp. 686-691. Mahwah, NJ: Erlbaum. [pdf]
  6. Lee, M.D., Chandrasena, L.H., & Navarro, D.J. (2002). Using cognitive decision models to prioritize e-mails. In W.G. Gray & C. D. Schunn, (Eds.), Proceedings of the 24th Annual Conference of the Cognitive Science Society, pp. 478-483. Mahwah, NJ: Erlbaum. [pdf]
  7. Navarro, D.J., & Lee, M.D. (2002). Commonalities and distinctions in featural stimulus representations. In W.G. Gray & C. D. Schunn, (Eds.), Proceedings of the 24th Annual Conference of the Cognitive Science Society, pp. 685-690. Mahwah, NJ: Erlbaum.
  8. Lee, M.D., Reilly, R.E., & Butavicius, M.A. (2003). An empirical evaluation of Chernoff faces, star glyphs, and spatial visualizations for binary data. In T. Pattison & B. Thomas, (Eds.), Proceeding of the Australian Symposium on Information Visualisation, pp. 1-10. Sydney: Australian Computer Society Inc.
  9. Navarro, D.J., & Lee, M.D. (2003). Combining dimensions and features in similarity-based representations. In S. Becker, S. Thrun and K. Obermayer (Eds.), Advances in Neural Information Processing Systems 15, pp. 59-66. Cambridge, MA: MIT Press. [pdf]
  10. Lee, M.D. (2004). An efficient method for the minimum description length evaluation of cognitive models. In K. Forbus, D. Gentner & T. Regier, (Eds.), Proceedings of the 26th Annual Conference of the Cognitive Science Society, pp. 807-812. Mahwah, NJ: Erlbaum. [pdf]
  11. Webb, M.R., & Lee, M.D. (2004). Modeling individual differences in category learning. In K. Forbus, D. Gentner & T. Regier, (Eds.), Proceedings of the 26th Annual Conference of the Cognitive Science Society, pp. 1440-1445. Mahwah, NJ: Erlbaum. [pdf]
  12. Lee, M.D., O’Connor, T.A., & Welsh, M.B. (2004). Decision-making on the full-information secretary problem. In K. Forbus, D. Gentner & T. Regier, (Eds.), Proceedings of the 26th Annual Conference of the Cognitive Science Society, pp. 819-824. Mahwah, NJ: Erlbaum. [pdf]
  13. Malhotra, V., Lee, M.D., & Khurana, A.K. (2004). Decisions and uncertainty management: Expertise Matters. SPE paper 88511 in Proceedings of the 2004 SPE Asia Pacific Oil and Gas Conference and Exhibition. Perth, Australia: SPE.
  14. Welsh, M.B., Begg, S.H., Bratvold, R.B., & Lee, M.D. (2004). Problems with the elicitation of uncertainty. SPE paper 90338 in Proceedings of the 80th Annual Technical Conference and Exhibition of the Society of Petroleum Engineers. Richardson, TX: SPE.
  15. Lee, M.D., Pincombe, B.M., & Welsh, M.B. (2005). An empirical evaluation of models of text document similarity. In B.G. Bara, L.W. Barsalou & M. Bucciarelli, (Eds.),  Proceedings of the 27th Annual Conference of the Cognitive Science Society, pp. 1254-1259. Mahwah, NJ: Erlbaum. [pdf]
  16. Navarro, D.J., Griffiths, T.L., Steyvers, M., & Lee, M.D. (2005). Modeling individual differences with Dirichlet processes In B.G. Bara, L.W. Barsalou & M. Bucciarelli, (Eds.),  Proceedings of the 27th Annual Conference of the Cognitive Science Society, pp. 1594-1599. Mahwah, NJ: Erlbaum. [pdf]
  17. Navarro, D.J., Lee, M.D., & Nikkerud, H. (2005). Learned categorical perception for natural faces. In B.G. Bara, L.W. Barsalou & M. Bucciarelli, (Eds.),  Proceedings of the 27th Annual Conference of the Cognitive Science Society, pp. 1600-1605. Mahwah, NJ: Erlbaum. [pdf]
  18. Navarro, D.J., & Lee, M.D. (2005). An application of minimum description length clustering to partitioning learning curves. Proceedings of the 2005 IEEE International Symposium on Information Theory, pp. 587-591. Piscataway, NJ: IEEE. [pdf]
  19. Lee, M.D., Vast, R.L., & Butavicius, M.A. (2006). Face matching under time pressure and task demands. In R. Sun (Ed.), Proceedings of the 28th Annual Conference of the Cognitive Science Society, pp. 1675-1680. Mahwah, NJ: Erlbaum. [pdf]
  20. Campbell, J., & Lee, M.D. (2006). The effect of feedback and financial reward on human performance solving ‘secretary’ problems.  In R. Sun (Ed.), Proceedings of the 28th Annual Conference of the Cognitive Science Society, pp. 1068-1073. Mahwah, NJ: Erlbaum. [pdf]
  21. Mackie, S.I., Welsh, M.B., & Lee, M.D. (2006). An oil and gas decision-making taxonomy. SPE paper 100699 in Proceedings of the 2006 SPE Asia Pacific Oil and Gas Conference and Exhibition. Adelaide, Australia: SPE.
  22. Lee, M.D., Fuss, I.G, & Navarro, D.J. (2006). A Bayesian approach to diffusion models of decision-making and response time. In B. Schölkopf, J.C. Platt, & T. Hoffman (Eds.), Advances in Neural Information Processing Systems 19, pp. 809-815. Cambridge, MA: MIT Press. [pdf]
  23. Vanpaemel, W., & Lee, M.D. (2007). A model of building representations for category learning.  In D. McNamara and G. Trafton (Eds.), Proceedings of the 29th Annual Conference of the Cognitive Science Society, pp. 1605-1610. Austin, TX: Cognitive Science Society. [pdf]
  24. Newell, B.R., Collins, P., & Lee, M.D. (2007). Adjusting the spanner: Testing an evidence accumulation model of decision making. In D. McNamara and G. Trafton (Eds.), Proceedings of the 29th Annual Conference of the Cognitive Science Society, pp. 535-538. Austin, TX: Cognitive Science Society. [pdf]
  25. Navarro, D.J, Lee, M.D., Dry, M.J, & Schultz, B. (2008). Extending and testing the Bayesian theory of generalization. In V. Sloutsky, B. Love, & K. McRae (Eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society, pp. 1746-1751. Austin, TX: Cognitive Science Society. [pdf]
  26. Zeigenfuse, M.D., & Lee, M.D. (2008). Finding feature representations of stimuli: Combining feature generation and similarity judgment tasks. In V. Sloutsky, B. Love, & K. McRae (Eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society, pp. 1825-1830. Austin, TX: Cognitive Science Society. [pdf]
  27. Vandekerckhove, J., Tuerlinckx, F., & Lee, M.D. (2008). A Bayesian approach to diffusion process models of decision-making. In V. Sloutsky, B. Love, & K. McRae (Eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society, pp. 1429-1434. Austin, TX: Cognitive Science Society. [pdf]
  28. Welsh, M.B., Lee, M.D., & Begg, S.H. (2008). More-Or-Less Elicitation (MOLE): Testing a heuristic elicitation model. In V. Sloutsky, B. Love, & K. McRae (Eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society, pp. 493-498. Austin, TX: Cognitive Science Society. [pdf]
  29. Rubin, T.N., Lee, M.D., & Chubb, C.F. (2008). Hierarchical Bayesian modeling of individual differences in texture discrimination. In V. Sloutsky, B. Love, & K. McRae (Eds.), Proceedings of the 30th Annual Conference of the Cognitive Science Society, pp. 1404-1409 Austin, TX: Cognitive Science Society. [pdf]
  30. Lee, M.D., & Habibi, A. (2009). A cyclic sequential sampling model of bistable auditory perception. In N. Taatgen, H. van Rijn, J. Nerbonne, & L. Shonmaker (Eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society, pp. 2669-2674. Austin, TX: Cognitive Science Society. [pdf]
  31. Pooley, J.P., Lee, M.D., & Shankle, W.R. (2009). Recognition memory deficits in Alzheimer’s disease: Modeling clinical groups and individual patients. In N. Taatgen, H. van Rijn, J. Nerbonne, & L. Shonmaker (Eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society, pp. 2849-2954. Austin, TX: Cognitive Science Society. [pdf]
  32. Zeigenfuse, M.D., & Lee, M.D. (2009). Bayesian nonparametric modeling of individual differences: A case study using decision-making on bandit problems.  In N. Taatgen, H. van Rijn, J. Nerbonne, & L. Shonmaker (Eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society, pp. 1412-1415. Austin, TX: Cognitive Science Society. [pdf]
  33. Welsh, M.B., Lee, M.D., & Begg, S.H. (2009). Repeated judgments in elicitation tasks: Efficacy of the MOLE method. In N. Taatgen, H. van Rijn, J. Nerbonne, & L. Shonmaker (Eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society, pp. 1529-1534 Austin, TX: Cognitive Science Society. [pdf]
  34. Newell, B.R., & Lee, M.D. (2009). Learning to adapt evidence thresholds in decision making. In N. Taatgen, H. van Rijn, J. Nerbonne, & L. Shonmaker (Eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society, pp. 473-478. Austin, TX: Cognitive Science Society. [pdf]
  35. Dry, M.J., Navarro, D.J., Preiss, A.K., & Lee, M.D. (2009). The perceptual organization of point constellations. In N. Taatgen, H. van Rijn, J. Nerbonne, & L. Shonmaker (Eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society, pp. 1151-1156. Austin, TX: Cognitive Science Society.  [pdf]
  36. Lee, M.D., Grothe, E., & Steyvers, M. (2009). Conjunction and disjunction fallacies in prediction markets.  In N. Taatgen, H. van Rijn, J. Nerbonne, & L. Shonmaker (Eds.), Proceedings of the 31st Annual Conference of the Cognitive Science Society, pp. 1639-1644. Austin, TX: Cognitive Science Society. [pdf]
  37. Lee, M.D., Zhang, S., Munro. M.N., & Steyvers, M. (2009). Using heuristic models to understand human and optimal decision-making on bandit problems. In A. Howes, D. Peebles, R. Cooper (Eds.), 9th International Conference on Cognitive Modeling – ICCM2009, Manchester, UK. [pdf]
  38. Miller, B., Hemmer, P., Steyvers, M., & Lee, M.D. (2009). The wisdom of crowds in rank ordering problems. In A. Howes, D. Peebles, & R. Cooper (Eds.), 9th International Conference on Cognitive Modeling – ICCM2009, Manchester, UK. [pdf]
  39. Zhang, S., Lee, M.D., & Munro. M.N. (2009). Human and optimal exploration and exploitation in bandit problems. In A. Howes, D. Peebles, & R. Cooper (Eds.), 9th International Conference on Cognitive Modeling – ICCM2009, Manchester, UK. [pdf]
  40. Steyvers, M., Lee, M.D., Miller, B., & Hemmer, P. (2009). The wisdom of crowds in the recollection of order information. In Y. Bengio, D. Schuurmans, J. Lafferty, C. K. I. Williams, & A. Culotta (Eds.), Advances in Neural Information Processing Systems 22, pp. 1785-1793. Cambridge: MA:  MIT Press. [pdf]
  41. Stephens, R.G., Navarro, D.J., Dunn, J.C., & Lee, M.D. (2009). The effect of causal strength on the use of causal and similarity-based information in feature inference. In ASC09: Proceedings of the 9th Conference of the Australasian Society for Cognitive Science. Edited by Wayne Christensen, Elizabeth Schier, and John Sutton. Sydney: Macquarie Centre for Cognitive Science. [pdf]
  42. Lee, M.D., & Shi, J. (2010).  The accuracy of small-group estimation and the wisdom of crowds. In R. Catrambone, & S. Ohlsson (Eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society, pp. 1124-1129. Austin, TX: Cognitive Science Society. [pdf]
  43. Lee, M.D., & Wetzels, R. (2010). Individual differences in attention during category learning. In R. Catrambone, & S. Ohlsson (Eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society, pp. 387-392. Austin, TX: Cognitive Science Society. [pdf]
  44. Zhang, S., & Lee, M.D., (2010). Cognitive models and the wisdom of crowds: A case study using the bandit problem. In R. Catrambone, & S. Ohlsson (Eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society, pp. 1118-1123. Austin, TX: Cognitive Science Society. [pdf]
  45. Zeigenfuse, M.D., & Lee, M.D. (2010). Heuristics for choosing features to represent stimuli. In R. Catrambone, & S. Ohlsson (Eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society, pp. 1565-1570. Austin, TX: Cognitive Science Society. [pdf]
  46. Pooley, J.P., Lee, M.D., & Shankle, W.R. (2010). Modeling change in recognition bias with the progression of Alzheimer’s. In R. Catrambone, & S. Ohlsson (Eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society, pp. 103-108. Austin, TX: Cognitive Science Society. [pdf]
  47. Yi, S.K., Steyvers, M., Lee, M.D., & Dry, M.J. (2010). Wisdom of the crowds in minimum spanning tree problems. In R. Catrambone, & S. Ohlsson (Eds.), Proceedings of the 32nd Annual Conference of the Cognitive Science Society, pp. 1840-1845. Austin, TX: Cognitive Science Society. [pdf]
  48. Zhang, S, Lee, M.D., Yu, M., & Xin, J. (2011). Modeling category identification using sparse instance representation. In L. Carlson, C. Hölscher, & T.F. Shipley (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society, pp. 2574-2579. Austin, TX: Cognitive Science Society. [pdf]
  49. Zeigenfuse, M.D., & Lee, M.D. (2011). A comparison of three measures of the association between a feature and a concept.  In L. Carlson, C. Hölscher, & T.F. Shipley (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society, pp. 243-248. Austin, TX: Cognitive Science Society. [pdf]
  50. Lee, M.D., Steyvers, M., de Young, M., & Miller, B. (2011). A model-based approach to measuring expertise in ranking tasks. In L. Carlson, C. Hölscher, & T.F. Shipley (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society, pp. 1304-1309. Austin, TX: Cognitive Science Society. [pdf]
  51. Pooley, J.P., Lee, M.D., & Shankle, W.R. (2011). Modeling multitrial free recall with unknown rehearsal times. In L. Carlson, C. Hölscher, & T.F. Shipley (Eds.), Proceedings of the 33rd Annual Conference of the Cognitive Science Society, pp. 108-113. Austin, TX: Cognitive Science Society. [pdf]
  52. Asher, D., Zhang, S., Zaldivar, A., Lee, M.D., & Krichmar, J. (2012). Modeling individual differences in socioeconomic game playing. In N. Miyake, D. Peebles, & R. Cooper (Eds.), Proceedings of the 34th Annual Conference of the Cognitive Science Society, pp. 90-95. Austin, TX: Cognitive Science Society. [pdf]
  53. van Ravenzwaaij, D., Newell, B.R., Moore, C.P., & Lee, M.D. (in press). Using recognition in multi-attribute decision environments. In M. Knauff, M. Pauen, N. Sebanz, & I. Wachsmuth (Eds.), Proceedings of the 34th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society. Accepted 10-Apr-2013. [pdf]

Book Chapters

  1. Lee, M.D., & Navarro, D.J. (2005). Minimum description length and psychological clustering models. In P.D. Grünwald, I.J. Myung and M.A. Pitt (Eds.), Advances in Minimum Description Length: Theory and Applications, pp. 355-384. Cambridge, MA: MIT Press.
  2. Wagenmakers, E.-J., Lee, M.D., Lodewyckx, T., & Iverson, G. (2008). Bayesian versus frequentist inference. In H. Hoijtink, I. Klugkist, and P. Boelen (Eds.), Practical Evaluation of Informative Hypotheses, pp. 181-207. Springer: New York. [pdf]
  3. Lee, M.D., Loughlin, N., & Lundberg, I. (2011). Applying one-reason decision-making: The prioritization of literature searches. In G. Gigerenzer, R. Hertwig, and T. Pachur (Eds.),  Heuristics: The Foundations of Adaptive Behavior. Oxford University Press. (Reprinted from Australian Journal of Psychology, 54, 137-143).  [pdf]
  4. Butavicius, M.A. & Lee, M.D. (2011). An empirical evaluation of four data visualization techniques for displaying short news text similarities. In R. Dale, D. Burnham, & C.J. Stevens (Eds.), Human Communication Science: A Compendium, pp. 125-148. Sydney: ARC Research Network in Communication Science. (Reprinted from International Journal of Human-Computer Studies, 65 (11), 931-944). [pdf]
  5. Pachur, T., Raaijmakers, J. G. W., Davelaar, E. J., Daw, N. D., Dougherty, M. R., Hommel, B., Lee, M. D., Polyn, S. M., Ridderinkhof, K. R., Todd, P. M., & Wolfe, J. M. (2012). Unpacking cognitive search: Mechanisms and processes. In: P. M. Todd, T. T. Hills, & T. W. Robbins (eds.), Cognitive search: Evolution, algorithms, and the brain. Strüngmann Forum Reports, Vol. 9. Cambridge, MA: MIT Press. [pdf]

Reports

  1. Lee, M.D., & Vickers, D. (1998). Psychological approaches to data visualisation. Defence Science and Technology Organisation Research Report, DSTO-RR-0135. [link here]
  2. Lee, M.D. (1999). Algorithms for representing similarity data. Defence Science and Technology Organisation Research Report, DSTO-RR-0152. [link here]
  3. Dry, M., Lee, M.D., Vickers, D., & Huf, S. (2005). Psychological implications for submarine display design. Defence Science and Technology Organisation Technical Report, DSTO-TR-1766. [link here]
  4. Pooley, J.P., & Lee, M.D. (2012). A correction to the SIMPLE model of free recall. Institute for Mathematical and Behavioral Science, Technical Report MBS-12-04. [link here]

Other

  1. Lee, M.D. (2002). Book review of R. Decker and W. Gaul, Eds., Classification and Information Processing at the Turn of the Millenium. Journal of Classification, 19(1), 183-186.
  2. Obituary for Professor Douglas Vickers, The Advertiser, Saturday 18th December, 2004, p. 80.
  3. Obituary for Professor Douglas Vickers, The Adelaidean, Volume 13, Number 11, December 2004, p. 12. (with T. Nettelbeck)
  4. Storms, G., Navarro, D.J., & Lee, M.D. (2010). Introduction to the special issue on formal modeling of semantic concepts. Acta Psychologica, 133, 213-215. [pdf]

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