Dr. David Kellen
Research Interests:
Recognition memory, risky-choice, multinomial processing tree models, signal detection theory, cumulative prospect theory, configural weight models, and pretty much anything related to the development and implementation of measurement models for categorical data.
Publications:
Note: Due to racketeering copyright restrictions, these manuscripts are password protected. In any case, KELLEN might help you.
Singmann, H., Klauer, K. C., & Kellen, D. (in preparation). Claims of Intuitive Logic Revisited: New Data and a Bayesian Mixed-Model Comparison.
Kellen, D., Singmann, H., & Klauer K. C. (in preparation). Overdistribution in Source Memory: Memory Versus Guessing-Based Accounts
Pachur, T. & Kellen, D. (in preparation). Modeling Gain-Loss Asymmetries in Cumulative Prospect Theory
Castela, M., Kellen, D., Erdfelder, E.. & Hilbig, B. E. (submitted). The impact of subjective recognition experiences on recognition heuristic use: A multinomial processing tree approach.
Pachur, T., & Kellen, D. (in press). Modeling Gain-Loss Asymmetries in of Risky Choice: The Critical Role of Probability Weighting. In M. Knauff, M. Pauen, N. Sebanz, & I. Wachsmuth (Eds.), Proceedings of the 35th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society.
Singmann, H., Kellen, D., & Klauer, K. C. (in press). Investigating the Other-Race Effect of Germans towards Turks and Arabs using Multinomial Processing Tree Models. In M. Knauff, M. Pauen, N. Sebanz, & I. Wachsmuth (Eds.), Proceedings of the 35th Annual Conference of the Cognitive Science Society. Austin, TX: Cognitive Science Society.
Kellen, D., Klauer, K. C., & Singmann, H. (in press). On the Measurement of Criterion Noise in Signal Detection Theory: Reply to Benjamin (in press). Psychological Review.
Kellen, D., Klauer, K. C., & Bröder, A. (in press). Recognition Memory Models and Binary-Response ROCs:
A Comparison by Minimum Description Length. Psychonomic Bulletin & Review.
Bröder, A., Kellen, D., Schütz, J., & Rohrmeier, C. (in press). Validating a Two-High-Threshold Measurement Model for Confidence Rating Data in Recognition. Memory.
Singmann, H., & Kellen, D. (in press). MPTinR: Analysis of Multinomial Processing Tree models with R. Behavior Research Methods.
Kellen, D., Klauer, K. C., & Singmann, H. (2012). On the measurement of criterion noise in Signal Detection Theory: The case of recognition memory. Psychological Review, 119, 457-479.
Klauer, K. C., & Kellen, D. (2012). The Law of Categorical Judgment (Corrected) extended: A note on Rosner and Kochanski (2009). Psychological Review, 119, 216-220.
Klauer, K. C., & Kellen, D. (2011). The flexibility of models of recognition memory: An analysis by the minimum-description length principle. Journal of Mathematical Psychology, 55, 430-450. [2012 R. Duncan Luce Outstanding Paper Award]
Kellen, D., & Klauer, K. C. (2011). Evaluating models of recognition memory using first- and second-choice responses. Journal of Mathematical Psychology, 55, 251–266.
Klauer, K. C., & Kellen, D. (2011). Assessing the belief bias effect with ROCs: Reply to Dube, Rotello, and Heit (2010). Psychological Review, 118, 164-173.
Klauer, K. C., & Kellen, D. (2010). Toward a complete decision model of item and source recognition: A discrete-state approach. Psychonomic Bulletin & Review, 17, 465-478.
Invited Presentations:
Recognition memory modeling: From confidence ratings to item rankings, and back. June, 21st, 2012. Universität Basel (Prof. Hertwig / Prof. Rieskamp)
Recognition memory modeling: Beyond ROCs. September 29th, 2011. Mannheim University (Prof. Erdfelder)
Invited Workshops:
Data analysis and modeling methods using R. November 24th and December 8th. Mannheim University.
An introduction to R. August 6th and 13th, 2012. Universität Zürich
An introduction to R. October 19th and 24th, 2011. Mannheim University
Conference Presentations:
Kellen, D, Klauer, K. C., & Bröder, A. (2013, August). The flexibility of models of recognition memory: An analysis by the minimum-description length principle. Paper presented at the 46th Annual Meeting of the Society for Mathematical Psychology, Potsdam, Germany.
Kellen, D., Klauer, K. C., & Singmann, H. (2013, March). Measuring Criterion Noise in Signal Detection Theory: The Case of Recognition Memory. Paper presented at the Tagung experimentell arbeitender Psychologen 2013, Vienna, Austria, March, 2013.
Kellen, D. & Singmann, H. (2013, February) MPTinR: Multinomial Processing Tree Models in R. Paper to be presented at the International Workshop on Psychometric Computing, Zürich, Switzerland.
Kellen, D., & Klauer, K. C. (2012, April). The flexibility of models of recognition memory: An analysis by the minimum-description length principle. Paper presented at the Tagung experimentell arbeitender Psychologen 2012, Mannheim, Germany, April, 2012.
Kellen, D., Klauer, K. C., & Singmann, H. (2011, July). Beyond ROCs: Fitting and extending recognition memory models with multiple-alternative, multiple-response tasks. Paper presented at the 44th Annual Meeting of the Society for Mathematical Psychology, Boston, Massachusetts, July 2011.
Conference Posters:
Castela, M., Kellen, D., Erdfelder, E., Hilbig, B. E. (2013, August).The impact of subjective recognition experiences on recognition heuristic use: A multinomial processing tree approach. Poster presented at the 46th Annual Meeting of the Society for Mathematical Psychology, Potsdam, Germany.
Linzer, J., Kellen, D., Singmann, H., Klauer, K. C. (2013, August). Modeling Overdistribution in Source Memory: Memory versus Guessing-Based Accounts. Poster presented at the 46th Annual Meeting of the Society for Mathematical Psychology, Potsdam, Germany.
Kellen, D, Klauer, K. C., & Bröder, A. (2012, November). Recognition Memory Models and Binary-Response ROCs:
A Comparison by Minimum Description Length. Poster presented at the Annual Meeting of the Psychonomic Society, Minneapolis, Minnesota.
Singmann, H., Kellen, D., Hölzenbein, F., & Klauer, K. C. (2011, July). MPTinR: An (almost) complete R package for analyzing MPTs. Poster presented at the 44th Annual Meeting of the Society for Mathematical Psychology, Boston, Massachusetts.
Kellen, D. (2010, July). Model Selection in Recognition Memory. Poster presented at the 1st ESCOP Summer School in Computational and Mathematical Modeling of Cognition, Mallnitz, Österreich, July 2010.
Ad-hoc reviews:
Note: I always sign my reviews.
Research Institutions
Economic & Social Research Council (UK)
Journals
Cognitive Psychology
Experimental Psychology
Frontiers in Cognitive Science
Journal of Experimental Psychology: General
Psychological Review
Psychonomic Bulletin & Review
Office:
Institut für Psychologie der Albert-Ludwigs-Universität Freiburg
Engelbergerstr. 41
D-79085 Freiburg im Breisgau
Raum 4035, 4. OG
Email: david.kellen
psychologie
uni-freiburgde
If you're interested in my work, drop me a line or two, but please don't send me any Word attachments.
Seminar Classes 2011/2012:
Im giving a Social Psychology seminar in the 2011/2012 Winter Semester. There is a Sprechstunde (Mittwoch, 11.00-12.00 Uhr), but I am relatively tolerant with meeting outside of this schedule. If you need to come some other time, just send me an email (or show up) and I will see what I can do for you.
SOCIAL PSYCHOLOGY SEMINAR SoSE 2013
Potential bachelor/master students:
If you are interested in what I do, and would like to write your bachelor/master thesis with me, please feel free to write me an email. You can either work on some empirical work (running experiments and testing hypotheses) or do more theoretical work (simulations and reanalyses). In any case, you will be expected to learn and use R.
Fitting MPT models in R: the MPTinR package:
Henrik Singmann and I developed a R package to fit MPT models in a convenient manner. You can get it here. Future versions will have additional features (did somebody say hierarchical?) and will be faster as well (it already is). If you have any suggestions and/or problems, please contact us.
The good stuff:
A reading list on Bayesian methods
A letter from Luce and Steingrimssom discussing a fundamental problem in psychological research
Because we do not understand the brain very well we are constantly tempted to use the latest technology as a model for trying to understand it. In my childhood we were always assured that the brain was a telephone switchboard. ('What else could it be?') I was amused to see that Sherrington, the great British neuroscientist, thought that the brain worked like a telegraph system. Freud often compared the brain to hydraulic and electro-magnetic systems. Leibniz compared it to a mill, and I am told some of the ancient Greeks thought the brain functions like a catapult. At present, obviously, the metaphor is the digital computer. - John R. Searle, "Brains, Minds, and Science"
- "Suppose there are a series of little drawers in the brain..."
- "I have never seen any drawers in there"
- "They're very small"
- “No, I'm serious. If it wasn't for the bats, insects would take over the world.”
- “What, you mean like, replace world leaders and occupy positions of social and economic power?”