Literatur - Versionsgeschichte

Wehner am 16. März 2020 um 21:38 Uhr

2020-03-16T21:38:45Z

← Nächstältere Version		Version vom 16. März 2020, 23:38 Uhr
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	* Wilensky, U., & Resnick, M. (1999). Thinking in levels: A dynamic systems approach to making sense of the world. ''Journal of Science Education and technology, 8''(1), 3-19.		* Wilensky, U., & Resnick, M. (1999). Thinking in levels: A dynamic systems approach to making sense of the world. ''Journal of Science Education and technology, 8''(1), 3-19.
	* Woergoetter, F. & Porr, B. (2008) Reinforcement Learning. ''Scholarpedia, 3''(3):1448.		* Woergoetter, F. & Porr, B. (2008) Reinforcement Learning. ''Scholarpedia, 3''(3):1448.


			'''Statistische Grundbegriffe und Grundlagen multivariater Verfahren'''

			* Bock, J. (1998). ''Bestimmung des Stichprobenumfangs: Für biologische Experimente und kontrollierte klinische Studien''. München: Oldenbourg.
			* Bortz, J., & Schuster, C. (2016). ''Statistik für Human- und Sozialwissenschaftler''. Berlin: Springer.
			* Bühner, M. (2010). ''Einführung in die Test- und Fragebogenkonstruktion'' (3. Aufl.; Kapitel 6). München: Pearson Studium.
			* Clauß, G., Finze, F. R., & Partzsch, L. (2011). ''Grundlagen der Statistik für Soziologen, Pädagogen, Psychologen und Mediziner''. Frankfurt: Europa-Lehrmittel
			* Cohen, J. (2013). ''Statistical power analysis for the behavioral sciences''. Routledge.
			* Collingridge, D. S. (2013). A primer on quantitized data analysis and permutation testing. ''Journal of Mixed Methods Research'', 7(1), 81-97.
			* Eid, M., Gollwitzer, M., & Schmitt, M. (2017). ''Statistik und Forschungsmethoden''. Weinheim: Beltz.
			* Hayes, A. F., & Cai, L. (2007). Using heteroskedasticity-consistent standard error estimators in OLS regression: An introduction and software implementation. ''Behavior research methods'', 39(4), 709-722.
			* Heiler, S., & Weichselberger, K. (1969). Über den Permutationstest und ein daraus ableitbares Konfidenzintervall. ''Metrika'', 14(1), 232-248.
			* Holling, H. & Gediga, G. (2010). ''Statistik - Deskriptive Verfahren''. Göttingen: Hogrefe.
			* Manly, B.F. (2018). ''Randomization, bootstrap and Monte Carlo Methods in biology''. Chapman and Hall/CRC
			* Rudolf, M. & Buse, J. (2020). ''Multivariate Verfahren. Eine praxisorientierte Einführung mit Anwendungsbeispielen''. Göttingen: Hogrefe.
			* Rudolf, M., & Kuhlisch, W. (2008). ''Biostatistik: Eine Einführung für Biowissenschaftler''. München: Pearson Studium.

Wehner am 25. Oktober 2018 um 16:24 Uhr

2018-10-25T16:24:11Z

← Nächstältere Version		Version vom 25. Oktober 2018, 18:24 Uhr
Zeile 36:		Zeile 36:
	* Lins, J., & Schöner, G. (2014). A neural approach to cognition based on dynamic field theory. In ''Neural Fields'' (pp. 319-339). Springer, Berlin, Heidelberg.		* Lins, J., & Schöner, G. (2014). A neural approach to cognition based on dynamic field theory. In ''Neural Fields'' (pp. 319-339). Springer, Berlin, Heidelberg.
	* Macho, S. (2002). Cognitive modeling with spreadsheets. ''Behavior Research Methods, Instruments, & Computers, 34''(1), 19-36.		* Macho, S. (2002). Cognitive modeling with spreadsheets. ''Behavior Research Methods, Instruments, & Computers, 34''(1), 19-36.
			* Mathys, C. D., Lomakina, E. I., Daunizeau, J., Iglesias, S., Brodersen, K. H., Friston, K. J., & Stephan, K. E. (2014). Uncertainty in perception and the Hierarchical Gaussian Filter. ''Frontiers in human neuroscience, 8'', 825.
	* Matzke, D., & Wagenmakers, E. J. (2009). Psychological interpretation of the ex-Gaussian and shifted Wald parameters: A diffusion model analysis. ''Psychonomic bulletin & review, 16''(5), 798-817.		* Matzke, D., & Wagenmakers, E. J. (2009). Psychological interpretation of the ex-Gaussian and shifted Wald parameters: A diffusion model analysis. ''Psychonomic bulletin & review, 16''(5), 798-817.
	* McClelland, J. L. (2009). The place of modeling in cognitive science. ''Topics in Cognitive Science, 1''(1), 11-38.		* McClelland, J. L. (2009). The place of modeling in cognitive science. ''Topics in Cognitive Science, 1''(1), 11-38.

Schäfer am 8. Oktober 2018 um 17:30 Uhr

2018-10-08T17:30:44Z

← Nächstältere Version		Version vom 8. Oktober 2018, 19:30 Uhr
Zeile 55:		Zeile 55:
	* Voss, A., Rothermund, K., Gast, A., & Wentura, D. (2013). Cognitive processes in associative and categorical priming: A diffusion model analysis. ''Journal of Experimental Psychology: General, 142''(2), 536.		* Voss, A., Rothermund, K., Gast, A., & Wentura, D. (2013). Cognitive processes in associative and categorical priming: A diffusion model analysis. ''Journal of Experimental Psychology: General, 142''(2), 536.
	* Wilensky, U., & Resnick, M. (1999). Thinking in levels: A dynamic systems approach to making sense of the world. ''Journal of Science Education and technology, 8''(1), 3-19.		* Wilensky, U., & Resnick, M. (1999). Thinking in levels: A dynamic systems approach to making sense of the world. ''Journal of Science Education and technology, 8''(1), 3-19.
	* Woergoetter, F. & Porr, B. (2008), ''Scholarpedia, 3''(3):1448.		* Woergoetter, F. & Porr, B. (2008) Reinforcement Learning. ''Scholarpedia, 3''(3):1448.

Schäfer am 8. Oktober 2018 um 17:29 Uhr

2018-10-08T17:29:06Z

← Nächstältere Version		Version vom 8. Oktober 2018, 19:29 Uhr
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	* Izhikevich, E. M. (2007). Solving the distal reward problem through linkage of STDP and dopamine signaling. ''Cerebral cortex, 17''(10), 2443-2452.		* Izhikevich, E. M. (2007). Solving the distal reward problem through linkage of STDP and dopamine signaling. ''Cerebral cortex, 17''(10), 2443-2452.
	* Kelso, J. S. (1997). ''Dynamic patterns: The self-organization of brain and behavior.'' MIT press.		* Kelso, J. S. (1997). ''Dynamic patterns: The self-organization of brain and behavior.'' MIT press.
			* Laird, J. E., Newell, A., & Rosenbloom, P. S. (1987). Soar: An architecture for general intelligence. ''Artificial intelligence, 33''(1), 1-64.
	* Lins, J., & Schöner, G. (2014). A neural approach to cognition based on dynamic field theory. In ''Neural Fields'' (pp. 319-339). Springer, Berlin, Heidelberg.		* Lins, J., & Schöner, G. (2014). A neural approach to cognition based on dynamic field theory. In ''Neural Fields'' (pp. 319-339). Springer, Berlin, Heidelberg.
	* Macho, S. (2002). Cognitive modeling with spreadsheets. ''Behavior Research Methods, Instruments, & Computers, 34''(1), 19-36.		* Macho, S. (2002). Cognitive modeling with spreadsheets. ''Behavior Research Methods, Instruments, & Computers, 34''(1), 19-36.
Zeile 39:		Zeile 40:
	* McKerchar, T. L., Green, L., Myerson, J., Pickford, T. S., Hill, J. C., & Stout, S. C. (2009). A comparison of four models of delay discounting in humans. ''Behavioural processes, 81''(2), 256-259.		* McKerchar, T. L., Green, L., Myerson, J., Pickford, T. S., Hill, J. C., & Stout, S. C. (2009). A comparison of four models of delay discounting in humans. ''Behavioural processes, 81''(2), 256-259.
	* Miller, R., Scherbaum, S., Heck, D. W., Goschke, T., & Enge, S. (2018). On the relation between the (censored) shifted Wald and the Wiener distribution as measurement models for choice response times. ''Applied psychological measurement, 42''(2), 116-135.		* Miller, R., Scherbaum, S., Heck, D. W., Goschke, T., & Enge, S. (2018). On the relation between the (censored) shifted Wald and the Wiener distribution as measurement models for choice response times. ''Applied psychological measurement, 42''(2), 116-135.
			* Portenier, C., & Gromes, W. (2005). ''Mathematik für Humanbiologen und Biologen''. Fachbereich Mathematik und Informatik Philipps-Universität Marburg.
	* Ratcliff, R., Smith, P. L., Brown, S. D., & McKoon, G. (2016). Diffusion decision model: current issues and history. ''Trends in cognitive sciences, 20''(4), 260-281.		* Ratcliff, R., Smith, P. L., Brown, S. D., & McKoon, G. (2016). Diffusion decision model: current issues and history. ''Trends in cognitive sciences, 20''(4), 260-281.
	* Ratcliff, R., Spieler, D., & Mckoon, G. (2000). Explicitly modeling the effects of aging on response time. ''Psychonomic Bulletin & Review, 7''(1), 1-25.		* Ratcliff, R., Spieler, D., & Mckoon, G. (2000). Explicitly modeling the effects of aging on response time. ''Psychonomic Bulletin & Review, 7''(1), 1-25.

Schäfer am 8. Oktober 2018 um 17:23 Uhr

2018-10-08T17:23:00Z

← Nächstältere Version		Version vom 8. Oktober 2018, 19:23 Uhr
Zeile 48:		Zeile 48:
	* Siegfried, R. (2009). Agent-based modeling and simulation. In Modeling and Simulation of Complex Systems (pp. 86–98).		* Siegfried, R. (2009). Agent-based modeling and simulation. In Modeling and Simulation of Complex Systems (pp. 86–98).
	* Schoner, G., & Kelso, J. A. (1988). Dynamic pattern generation in behavioral and neural systems. Science, 239(4847), 1513-1520.		* Schoner, G., & Kelso, J. A. (1988). Dynamic pattern generation in behavioral and neural systems. Science, 239(4847), 1513-1520.
			* Sun, R. (2008). Introduction to computational cognitive modeling. ''Cambridge handbook of computational psychology'', 3-19.
	* Tuller, B., Case, P., Ding, M., & Kelso, J. A. (1994). The nonlinear dynamics of speech categorization. ''Journal of Experimental Psychology: Human perception and performance, 20''(1), 3.		* Tuller, B., Case, P., Ding, M., & Kelso, J. A. (1994). The nonlinear dynamics of speech categorization. ''Journal of Experimental Psychology: Human perception and performance, 20''(1), 3.
	* Stephan, A., & Walter, S. (Eds.). (2013). ''Handbuch Kognitionswissenschaft.'' Springer-Verlag.		* Stephan, A., & Walter, S. (Eds.). (2013). ''Handbuch Kognitionswissenschaft.'' Springer-Verlag.

Schäfer am 8. Oktober 2018 um 17:16 Uhr

2018-10-08T17:16:46Z

← Nächstältere Version		Version vom 8. Oktober 2018, 19:16 Uhr
Zeile 18:		Zeile 18:
	* Anders, R., Alario, F., & Van Maanen, L. (2016). The shifted Wald distribution for response time data analysis. ''Psychological methods, 21''(3), 309.		* Anders, R., Alario, F., & Van Maanen, L. (2016). The shifted Wald distribution for response time data analysis. ''Psychological methods, 21''(3), 309.
	* Anderson, B. (2014). ''Computational neuroscience and cognitive modelling: a student's introduction to methods and procedures''. Sage.		* Anderson, B. (2014). ''Computational neuroscience and cognitive modelling: a student's introduction to methods and procedures''. Sage.
			* Anderson, J. R., Bothell, D., Byrne, M. D., Douglass, S., Lebiere, C., & Qin, Y. (2004). An integrated theory of the mind. ''Psychological review, 111''(4), 1036.
			* Anderson, J. R. (1996). ACT: A simple theory of complex cognition. ''American Psychologist, 51''(4), 355.
	* Andres, J.: Das allgemeine lineare Modell. In Edgar Erdfelder, Rainer Mausfeld, Thorsten Meiser & Georg Rudinger (Hrsg.), Handbuch quantitative Methoden, 1996 (S.185-200); Weinheim: Belz.		* Andres, J.: Das allgemeine lineare Modell. In Edgar Erdfelder, Rainer Mausfeld, Thorsten Meiser & Georg Rudinger (Hrsg.), Handbuch quantitative Methoden, 1996 (S.185-200); Weinheim: Belz.
	* Balota, D. A., & Yap, M. J. (2011). Moving beyond the mean in studies of mental chronometry: The power of response time distributional analyses. ''Current Directions in Psychological Science, 20''(3), 160-166.		* Balota, D. A., & Yap, M. J. (2011). Moving beyond the mean in studies of mental chronometry: The power of response time distributional analyses. ''Current Directions in Psychological Science, 20''(3), 160-166.
	* Bundesen, C., & Habekost, T. (2007). Models of attention.		* Bundesen, C., & Habekost, T. (2007). Models of attention.
	* Busemeyer, J. R., & Diederich, A. (2010). ''Cognitive modeling''. Sage.		* Busemeyer, J. R., & Diederich, A. (2010). ''Cognitive modeling''. Sage.
			* Domjan, M. (2014). ''The principles of learning and behavior''. Nelson Education.
	* Forstmann, B. U., Ratcliff, R., & Wagenmakers, E. J. (2016). Sequential sampling models in cognitive neuroscience: Advantages, applications, and extensions. ''Annual review of psychology, 67.''		* Forstmann, B. U., Ratcliff, R., & Wagenmakers, E. J. (2016). Sequential sampling models in cognitive neuroscience: Advantages, applications, and extensions. ''Annual review of psychology, 67.''
			* Gaschler, R. (2014). Kognitive Architektur. In M. A. Wirtz (Hrsg.), ''Dorsch – Lexikon der Psychologie'' (18. Aufl., S. 839). Bern: Verlag Hogrefe Verlag.
	* Goldstone, R. L., & Janssen, M. A. (2005). Computational models of collective behavior. ''Trends in cognitive sciences, 9''(9), 424-430.		* Goldstone, R. L., & Janssen, M. A. (2005). Computational models of collective behavior. ''Trends in cognitive sciences, 9''(9), 424-430.
	* Grimm, V., Revilla, E., Berger, U., Jeltsch, F., Mooij, W. M., Railsback, S. F., ... & DeAngelis, D. L. (2005). Pattern-oriented modeling of agent-based complex systems: lessons from ecology. ''Science, 310''(5750), 987-991.		* Grimm, V., Revilla, E., Berger, U., Jeltsch, F., Mooij, W. M., Railsback, S. F., ... & DeAngelis, D. L. (2005). Pattern-oriented modeling of agent-based complex systems: lessons from ecology. ''Science, 310''(5750), 987-991.
Zeile 38:		Zeile 42:
	* Ratcliff, R., Spieler, D., & Mckoon, G. (2000). Explicitly modeling the effects of aging on response time. ''Psychonomic Bulletin & Review, 7''(1), 1-25.		* Ratcliff, R., Spieler, D., & Mckoon, G. (2000). Explicitly modeling the effects of aging on response time. ''Psychonomic Bulletin & Review, 7''(1), 1-25.
	* Rey, G. D., & Wender, K. F. (2008). Neuronale Netze. ''Eine Einführung in die Grundlagen, Anwendungen und Datenauswertung.'' Huber, Bern.		* Rey, G. D., & Wender, K. F. (2008). Neuronale Netze. ''Eine Einführung in die Grundlagen, Anwendungen und Datenauswertung.'' Huber, Bern.
			* Rescorla, R. A. (2008) Rescorla-Wagner model. ''Scholarpedia, 3''(3):2237.
			* Rescorla, R. A., & Wagner, A. R. (1972). A theory of Pavlovian conditioning: Variations in the effectiveness of reinforcement and nonreinforcement. ''Classical conditioning II: Current research and theory, 2'', 64-99.
	* Rudolf, M., & Müller, J. (2012). ''Multivariate Verfahren: eine praxisorientierte Einführung mit Anwendungsbeispielen in SPSS.'' Hogrefe Verlag.		* Rudolf, M., & Müller, J. (2012). ''Multivariate Verfahren: eine praxisorientierte Einführung mit Anwendungsbeispielen in SPSS.'' Hogrefe Verlag.
	* Sandamirskaya, Y., Zibner, S. K., Schneegans, S., & Schöner, G. (2013). Using dynamic field theory to extend the embodiment stance toward higher cognition. ''New Ideas in Psychology, 31''(3), 322-339.		* Sandamirskaya, Y., Zibner, S. K., Schneegans, S., & Schöner, G. (2013). Using dynamic field theory to extend the embodiment stance toward higher cognition. ''New Ideas in Psychology, 31''(3), 322-339.
Zeile 46:		Zeile 52:
	* Voss, A., Rothermund, K., Gast, A., & Wentura, D. (2013). Cognitive processes in associative and categorical priming: A diffusion model analysis. ''Journal of Experimental Psychology: General, 142''(2), 536.		* Voss, A., Rothermund, K., Gast, A., & Wentura, D. (2013). Cognitive processes in associative and categorical priming: A diffusion model analysis. ''Journal of Experimental Psychology: General, 142''(2), 536.
	* Wilensky, U., & Resnick, M. (1999). Thinking in levels: A dynamic systems approach to making sense of the world. ''Journal of Science Education and technology, 8''(1), 3-19.		* Wilensky, U., & Resnick, M. (1999). Thinking in levels: A dynamic systems approach to making sense of the world. ''Journal of Science Education and technology, 8''(1), 3-19.
			* Woergoetter, F. & Porr, B. (2008), ''Scholarpedia, 3''(3):1448.

Wehner am 9. September 2018 um 16:46 Uhr

2018-09-09T16:46:20Z

← Nächstältere Version		Version vom 9. September 2018, 18:46 Uhr
Zeile 16:		Zeile 16:
	''' Kognitive Modellierung'''		''' Kognitive Modellierung'''

	* Anders, R., Alario, F~~. X~~., & Van Maanen, L. (2016). The shifted Wald distribution for response time data analysis. Psychological methods, 21(3), 309.		* Anders, R., Alario, F., & Van Maanen, L. (2016). The shifted Wald distribution for response time data analysis. ''Psychological methods, 21''(3), 309.
	* Anderson, B. (2014). Computational neuroscience and cognitive modelling: a student's introduction to methods and procedures. Sage.		* Anderson, B. (2014). ''Computational neuroscience and cognitive modelling: a student's introduction to methods and procedures''. Sage.
	* Andres, J.: Das allgemeine lineare Modell. In Edgar Erdfelder, Rainer Mausfeld, Thorsten Meiser & Georg Rudinger (Hrsg.), Handbuch quantitative Methoden, 1996 (S.185-200); Weinheim: Belz.		* Andres, J.: Das allgemeine lineare Modell. In Edgar Erdfelder, Rainer Mausfeld, Thorsten Meiser & Georg Rudinger (Hrsg.), Handbuch quantitative Methoden, 1996 (S.185-200); Weinheim: Belz.
			* Balota, D. A., & Yap, M. J. (2011). Moving beyond the mean in studies of mental chronometry: The power of response time distributional analyses. ''Current Directions in Psychological Science, 20''(3), 160-166.
	* Bundesen, C., & Habekost, T. (2007). Models of attention.		* Bundesen, C., & Habekost, T. (2007). Models of attention.
	* Busemeyer, J. R., & Diederich, A. (2010). Cognitive modeling. Sage.		* Busemeyer, J. R., & Diederich, A. (2010). ''Cognitive modeling''. Sage.
	* Balota, D. A., & Yap, M. J. (2011). Moving beyond the mean in studies of mental chronometry: The power of response time distributional analyses. Current Directions in Psychological Science, 20(3), 160–166.		* Forstmann, B. U., Ratcliff, R., & Wagenmakers, E. J. (2016). Sequential sampling models in cognitive neuroscience: Advantages, applications, and extensions. ''Annual review of psychology, 67.''
	* Bundesen, C., & Habekost, T. (2007). Models of attention.		* Goldstone, R. L., & Janssen, M. A. (2005). Computational models of collective behavior. ''Trends in cognitive sciences, 9''(9), 424-430.
	* Forstmann, B. U., Ratcliff, R., & Wagenmakers, E. J. (2016). Sequential sampling models in cognitive neuroscience: Advantages, applications, and extensions. Annual review of psychology, 67.		* Grimm, V., Revilla, E., Berger, U., Jeltsch, F., Mooij, W. M., Railsback, S. F., ... & DeAngelis, D. L. (2005). Pattern-oriented modeling of agent-based complex systems: lessons from ecology. ''Science, 310''(5750), 987-991.
	* Goldstone, R. L., & Janssen, M. A. (2005). Computational models of collective behavior. Trends in ~~Cognitive Sciences~~, 9(9), ~~424–430~~.		* Heathcote, A., Brown, S. D., & Wagenmakers, E. J. (2015). An introduction to good practices in cognitive modeling. In ''An introduction to model-based cognitive neuroscience'' (pp. 25-48). Springer, New York, NY.
	* Grimm, V., Revilla, E., Berger, U., Jeltsch, F., Mooij, W. M., Railsback, S. F., … DeAngelis, D. L. (2005). Pattern-oriented modeling of agent-based complex systems: ~~Lessons~~ from ecology. Science, 310(5750), ~~987–991~~.		* Honing, H. (2006). The role of surprise in theory testing: Some preliminary observations. In ''Proceedings of the international conference on music perception and cognition'' (pp. 38-42).
	* Heathcote, A., & Brown, S. (2015). An ~~Introduction~~ to ~~Good Practices~~ in ~~Cognitive~~ An ~~Introduction~~ to ~~Good Practices in Cognitive Modeling~~. Springer.		* Izhikevich, E. M. (2007). Solving the distal reward problem through linkage of STDP and dopamine signaling. ''Cerebral cortex, 17''(10), 2443-2452.
	* Honing, H. (2006). The role of surprise in theory testing: Some preliminary observations. In Proceedings of the international conference on music perception and cognition (pp. ~~38–42~~).		* Kelso, J. S. (1997). ''Dynamic patterns: The self-organization of brain and behavior.'' MIT press.
	* Izhikevich, E. M. (2007). Solving the distal reward problem through linkage of STDP and dopamine signaling. Cerebral ~~Cortex~~, 17(10), ~~2443–2452~~.		* Lins, J., & Schöner, G. (2014). A neural approach to cognition based on dynamic field theory. In ''Neural Fields'' (pp. 319-339). Springer, Berlin, Heidelberg.
	* Kelso, J~~. A~~. S. (1997). Dynamic ~~Patterns~~: The ~~Self~~-~~Organization~~ of ~~Behavior~~.		* Macho, S. (2002). Cognitive modeling with spreadsheets. ''Behavior Research Methods, Instruments, & Computers, 34''(1), 19-36.
	* Lins, J., & Schöner, G. (2014). A ~~Neural Approach~~ to ~~Cognition Based~~ on ~~Dynamic Field Theory~~. Neural Fields, ~~319–339~~.		* Matzke, D., & Wagenmakers, E. J. (2009). Psychological interpretation of the ex-Gaussian and shifted Wald parameters: A diffusion model analysis. ''Psychonomic bulletin & review, 16''(5), 798-817.
	* Macho, S. (2002). Cognitive modeling with spreadsheets. Behavior Research Methods, Instruments, ~~and~~ Computers, 34(1), ~~19–36~~.		* McClelland, J. L. (2009). The place of modeling in cognitive science. ''Topics in Cognitive Science, 1''(1), 11-38.
	* Matzke, D., & Wagenmakers, E. J. (2009). Psychological interpretation of the ex-Gaussian and shifted Wald parameters: A diffusion model analysis. Psychonomic bulletin & review, 16(5), 798-817.		* McKerchar, T. L., Green, L., Myerson, J., Pickford, T. S., Hill, J. C., & Stout, S. C. (2009). A comparison of four models of delay discounting in humans. ''Behavioural processes, 81''(2), 256-259.
	* McClelland, J. L. (2009). The ~~Place~~ of ~~Modeling~~ in ~~Cognitive Science~~. Topics in Cognitive Science, 1(1), ~~11–38~~.		* Miller, R., Scherbaum, S., Heck, D. W., Goschke, T., & Enge, S. (2018). On the relation between the (censored) shifted Wald and the Wiener distribution as measurement models for choice response times. ''Applied psychological measurement, 42''(2), 116-135.
	* McKerchar, T. L., Green, L., Myerson, J., Pickford, T. S., Hill, J. C., & Stout, S. C. (2009). A comparison of four models of delay discounting in humans. Behavioural processes, 81(2), 256-259.		* Ratcliff, R., Smith, P. L., Brown, S. D., & McKoon, G. (2016). Diffusion decision model: current issues and history. ''Trends in cognitive sciences, 20''(4), 260-281.
	* Miller, R., Scherbaum, S., Heck, D. W., Goschke, T., & Enge, S. (~~2017~~). On the relation between the (censored) shifted Wald and the Wiener distribution as measurement models for choice response times. Applied ~~Psychological Measurement~~, ~~0146621617710465~~.		* Ratcliff, R., Spieler, D., & Mckoon, G. (2000). Explicitly modeling the effects of aging on response time. ''Psychonomic Bulletin & Review, 7''(1), 1-25.
	* Ratcliff, R., Smith, P. L., Brown, S. D., & McKoon, G. (2016). Diffusion ~~Decision Model~~: ~~Current Issues~~ and ~~History~~. Trends in ~~Cognitive Sciences~~, 20(4), ~~260–281~~.		* Rey, G. D., & Wender, K. F. (2008). Neuronale Netze. ''Eine Einführung in die Grundlagen, Anwendungen und Datenauswertung.'' Huber, Bern.
	* Ratcliff, R., Spieler, D., & Mckoon, G. (2000). Explicitly modeling the effects of aging on response time. Psychonomic Bulletin & Review, 7(1), 1-25.		* Rudolf, M., & Müller, J. (2012). ''Multivariate Verfahren: eine praxisorientierte Einführung mit Anwendungsbeispielen in SPSS.'' Hogrefe Verlag.
	* Rey, G. D., & Wender, K. F. (2008). Neuronale Netze~~: eine~~ Einführung in die Grundlagen, Anwendungen und Datenauswertung.		* Sandamirskaya, Y., Zibner, S. K., Schneegans, S., & Schöner, G. (2013). Using dynamic field theory to extend the embodiment stance toward higher cognition. ''New Ideas in Psychology, 31''(3), 322-339.
	* Rudolf, M., & Müller, J. (2012). Multivariate Verfahren: eine praxisorientierte Einführung mit Anwendungsbeispielen in SPSS. Hogrefe Verlag.		* Siegfried, R. (2009). Agent-based modeling and simulation. In Modeling and Simulation of Complex Systems (pp. 86–98).
	* Sandamirskaya, Y., Zibner, S. K~~. U~~., Schneegans, S., & Schöner, G. (2013). Using ~~Dynamic Field Theory~~ to extend the embodiment stance toward higher cognition. New Ideas in Psychology, 31(3), ~~322–339.~~		* Schoner, G., & Kelso, J. A. (1988). Dynamic pattern generation in behavioral and neural systems. Science, 239(4847), 1513-1520.
	* Sequential sampling models in cognitive neuroscience: Advantages, applications, and extensions. Annual review of psychology, 67.		* Tuller, B., Case, P., Ding, M., & Kelso, J. A. (1994). The nonlinear dynamics of speech categorization. ''Journal of Experimental Psychology: Human perception and performance, 20''(1), 3.
	* Siegfried, R. (2009). Agent-based modeling and simulation. In Modeling and Simulation of Complex Systems (pp. 86–98).		* Stephan, A., & Walter, S. (Eds.). (2013). ''Handbuch Kognitionswissenschaft.'' Springer-Verlag.
	* Schoner, G., & Kelso, J. A. (1988). Dynamic pattern generation in behavioral and neural systems. Science, 239(4847), ~~1513–1520.~~		* Voss, A., Rothermund, K., Gast, A., & Wentura, D. (2013). Cognitive processes in associative and categorical priming: A diffusion model analysis. ''Journal of Experimental Psychology: General, 142''(2), 536.
	* Siegfried, R. (2009). Agent-~~based modeling and simulation. In Modeling and Simulation of Complex Systems (pp. 86–98)~~.		* Wilensky, U., & Resnick, M. (1999). Thinking in levels: A dynamic systems approach to making sense of the world. ''Journal of Science Education and technology, 8''(1), 3-19.
	* Tuller, B., Case, P., Ding, M., & Kelso, J. A~~. S~~. (1994). The nonlinear dynamics of speech categorization. Journal of Experimental Psychology: Human ~~Perception~~ and ~~Performance~~, 20(1), ~~3–16~~.
	* Stephan, A., & Walter, S. (Eds.). (2013). Handbuch Kognitionswissenschaft. Springer-Verlag.
	* Voss, A., Rothermund, K., Gast, A., & Wentura, D. (2013). Cognitive processes in associative and categorical priming: A diffusion model analysis. Journal of Experimental Psychology: General, 142(2), 536.
	* Wilensky, U., & Resnick, M. (1999). ~~Springer~~ Thinking in ~~Levels~~: A ~~Dynamic Systems Approach~~ to ~~Making Sense~~ of the ~~World Thinking in Levels: A Dynamic Systems Approach to Making Sense of the World~~. ~~Source:~~ Journal of Science Education and ~~Technology Journal of Science Education and Technology~~, 8(1), ~~3–19~~.

Wehner am 28. August 2018 um 14:21 Uhr

2018-08-28T14:21:10Z

← Nächstältere Version		Version vom 28. August 2018, 16:21 Uhr
Zeile 16:		Zeile 16:
	''' Kognitive Modellierung'''		''' Kognitive Modellierung'''

			* Anders, R., Alario, F. X., & Van Maanen, L. (2016). The shifted Wald distribution for response time data analysis. Psychological methods, 21(3), 309.
			* Anderson, B. (2014). Computational neuroscience and cognitive modelling: a student's introduction to methods and procedures. Sage.
			* Andres, J.: Das allgemeine lineare Modell. In Edgar Erdfelder, Rainer Mausfeld, Thorsten Meiser & Georg Rudinger (Hrsg.), Handbuch quantitative Methoden, 1996 (S.185-200); Weinheim: Belz.
			* Bundesen, C., & Habekost, T. (2007). Models of attention.
			* Busemeyer, J. R., & Diederich, A. (2010). Cognitive modeling. Sage.
	* Balota, D. A., & Yap, M. J. (2011). Moving beyond the mean in studies of mental chronometry: The power of response time distributional analyses. Current Directions in Psychological Science, 20(3), 160–166.		* Balota, D. A., & Yap, M. J. (2011). Moving beyond the mean in studies of mental chronometry: The power of response time distributional analyses. Current Directions in Psychological Science, 20(3), 160–166.
	* Bundesen, C., & Habekost, T. (2007). Models of attention.		* Bundesen, C., & Habekost, T. (2007). Models of attention.
			* Forstmann, B. U., Ratcliff, R., & Wagenmakers, E. J. (2016). Sequential sampling models in cognitive neuroscience: Advantages, applications, and extensions. Annual review of psychology, 67.
	* Goldstone, R. L., & Janssen, M. A. (2005). Computational models of collective behavior. Trends in Cognitive Sciences, 9(9), 424–430.		* Goldstone, R. L., & Janssen, M. A. (2005). Computational models of collective behavior. Trends in Cognitive Sciences, 9(9), 424–430.
	* Grimm, V., Revilla, E., Berger, U., Jeltsch, F., Mooij, W. M., Railsback, S. F., … DeAngelis, D. L. (2005). Pattern-oriented modeling of agent-based complex systems: Lessons from ecology. Science, 310(5750), 987–991.		* Grimm, V., Revilla, E., Berger, U., Jeltsch, F., Mooij, W. M., Railsback, S. F., … DeAngelis, D. L. (2005). Pattern-oriented modeling of agent-based complex systems: Lessons from ecology. Science, 310(5750), 987–991.
Zeile 26:		Zeile 32:
	* Lins, J., & Schöner, G. (2014). A Neural Approach to Cognition Based on Dynamic Field Theory. Neural Fields, 319–339.		* Lins, J., & Schöner, G. (2014). A Neural Approach to Cognition Based on Dynamic Field Theory. Neural Fields, 319–339.
	* Macho, S. (2002). Cognitive modeling with spreadsheets. Behavior Research Methods, Instruments, and Computers, 34(1), 19–36.		* Macho, S. (2002). Cognitive modeling with spreadsheets. Behavior Research Methods, Instruments, and Computers, 34(1), 19–36.
	* ~~Mcclelland~~, J. L. (2009). The Place of Modeling in Cognitive Science. Topics in Cognitive Science, 1(1), 11–38.		* Matzke, D., & Wagenmakers, E. J. (2009). Psychological interpretation of the ex-Gaussian and shifted Wald parameters: A diffusion model analysis. Psychonomic bulletin & review, 16(5), 798-817.
			* McClelland, J. L. (2009). The Place of Modeling in Cognitive Science. Topics in Cognitive Science, 1(1), 11–38.
			* McKerchar, T. L., Green, L., Myerson, J., Pickford, T. S., Hill, J. C., & Stout, S. C. (2009). A comparison of four models of delay discounting in humans. Behavioural processes, 81(2), 256-259.
			* Miller, R., Scherbaum, S., Heck, D. W., Goschke, T., & Enge, S. (2017). On the relation between the (censored) shifted Wald and the Wiener distribution as measurement models for choice response times. Applied Psychological Measurement, 0146621617710465.
	* Ratcliff, R., Smith, P. L., Brown, S. D., & McKoon, G. (2016). Diffusion Decision Model: Current Issues and History. Trends in Cognitive Sciences, 20(4), 260–281.		* Ratcliff, R., Smith, P. L., Brown, S. D., & McKoon, G. (2016). Diffusion Decision Model: Current Issues and History. Trends in Cognitive Sciences, 20(4), 260–281.
			* Ratcliff, R., Spieler, D., & Mckoon, G. (2000). Explicitly modeling the effects of aging on response time. Psychonomic Bulletin & Review, 7(1), 1-25.
	* Rey, G. D., & Wender, K. F. (2008). Neuronale Netze: eine Einführung in die Grundlagen, Anwendungen und Datenauswertung.		* Rey, G. D., & Wender, K. F. (2008). Neuronale Netze: eine Einführung in die Grundlagen, Anwendungen und Datenauswertung.
			* Rudolf, M., & Müller, J. (2012). Multivariate Verfahren: eine praxisorientierte Einführung mit Anwendungsbeispielen in SPSS. Hogrefe Verlag.
	* Sandamirskaya, Y., Zibner, S. K. U., Schneegans, S., & Schöner, G. (2013). Using Dynamic Field Theory to extend the embodiment stance toward higher cognition. New Ideas in Psychology, 31(3), 322–339.		* Sandamirskaya, Y., Zibner, S. K. U., Schneegans, S., & Schöner, G. (2013). Using Dynamic Field Theory to extend the embodiment stance toward higher cognition. New Ideas in Psychology, 31(3), 322–339.
			* Sequential sampling models in cognitive neuroscience: Advantages, applications, and extensions. Annual review of psychology, 67.
			* Siegfried, R. (2009). Agent-based modeling and simulation. In Modeling and Simulation of Complex Systems (pp. 86–98).
	* Schoner, G., & Kelso, J. A. (1988). Dynamic pattern generation in behavioral and neural systems. Science, 239(4847), 1513–1520.		* Schoner, G., & Kelso, J. A. (1988). Dynamic pattern generation in behavioral and neural systems. Science, 239(4847), 1513–1520.
	* Siegfried, R. (2009). Agent-based modeling and simulation. In Modeling and Simulation of Complex Systems (pp. 86–98).		* Siegfried, R. (2009). Agent-based modeling and simulation. In Modeling and Simulation of Complex Systems (pp. 86–98).
	* Tuller, B., Case, P., Ding, M., & Kelso, J. A. S. (1994). The nonlinear dynamics of speech categorization. Journal of Experimental Psychology: Human Perception and Performance, 20(1), 3–16.		* Tuller, B., Case, P., Ding, M., & Kelso, J. A. S. (1994). The nonlinear dynamics of speech categorization. Journal of Experimental Psychology: Human Perception and Performance, 20(1), 3–16.
			* Stephan, A., & Walter, S. (Eds.). (2013). Handbuch Kognitionswissenschaft. Springer-Verlag.
			* Voss, A., Rothermund, K., Gast, A., & Wentura, D. (2013). Cognitive processes in associative and categorical priming: A diffusion model analysis. Journal of Experimental Psychology: General, 142(2), 536.
	* Wilensky, U., & Resnick, M. (1999). Springer Thinking in Levels: A Dynamic Systems Approach to Making Sense of the World Thinking in Levels: A Dynamic Systems Approach to Making Sense of the World. Source: Journal of Science Education and Technology Journal of Science Education and Technology, 8(1), 3–19.		* Wilensky, U., & Resnick, M. (1999). Springer Thinking in Levels: A Dynamic Systems Approach to Making Sense of the World Thinking in Levels: A Dynamic Systems Approach to Making Sense of the World. Source: Journal of Science Education and Technology Journal of Science Education and Technology, 8(1), 3–19.

Wehner am 28. August 2018 um 13:44 Uhr

2018-08-28T13:44:01Z

← Nächstältere Version		Version vom 28. August 2018, 15:44 Uhr
Zeile 15:		Zeile 15:

	''' Kognitive Modellierung'''		''' Kognitive Modellierung'''

			* Balota, D. A., & Yap, M. J. (2011). Moving beyond the mean in studies of mental chronometry: The power of response time distributional analyses. Current Directions in Psychological Science, 20(3), 160–166.
			* Bundesen, C., & Habekost, T. (2007). Models of attention.
			* Goldstone, R. L., & Janssen, M. A. (2005). Computational models of collective behavior. Trends in Cognitive Sciences, 9(9), 424–430.
			* Grimm, V., Revilla, E., Berger, U., Jeltsch, F., Mooij, W. M., Railsback, S. F., … DeAngelis, D. L. (2005). Pattern-oriented modeling of agent-based complex systems: Lessons from ecology. Science, 310(5750), 987–991.
			* Heathcote, A., & Brown, S. (2015). An Introduction to Good Practices in Cognitive An Introduction to Good Practices in Cognitive Modeling. Springer.
			* Honing, H. (2006). The role of surprise in theory testing: Some preliminary observations. In Proceedings of the international conference on music perception and cognition (pp. 38–42).
			* Izhikevich, E. M. (2007). Solving the distal reward problem through linkage of STDP and dopamine signaling. Cerebral Cortex, 17(10), 2443–2452.
			* Kelso, J. A. S. (1997). Dynamic Patterns: The Self-Organization of Behavior.
			* Lins, J., & Schöner, G. (2014). A Neural Approach to Cognition Based on Dynamic Field Theory. Neural Fields, 319–339.
			* Macho, S. (2002). Cognitive modeling with spreadsheets. Behavior Research Methods, Instruments, and Computers, 34(1), 19–36.
			* Mcclelland, J. L. (2009). The Place of Modeling in Cognitive Science. Topics in Cognitive Science, 1(1), 11–38.
			* Ratcliff, R., Smith, P. L., Brown, S. D., & McKoon, G. (2016). Diffusion Decision Model: Current Issues and History. Trends in Cognitive Sciences, 20(4), 260–281.
			* Rey, G. D., & Wender, K. F. (2008). Neuronale Netze: eine Einführung in die Grundlagen, Anwendungen und Datenauswertung.
			* Sandamirskaya, Y., Zibner, S. K. U., Schneegans, S., & Schöner, G. (2013). Using Dynamic Field Theory to extend the embodiment stance toward higher cognition. New Ideas in Psychology, 31(3), 322–339.
			* Schoner, G., & Kelso, J. A. (1988). Dynamic pattern generation in behavioral and neural systems. Science, 239(4847), 1513–1520.
			* Siegfried, R. (2009). Agent-based modeling and simulation. In Modeling and Simulation of Complex Systems (pp. 86–98).
			* Tuller, B., Case, P., Ding, M., & Kelso, J. A. S. (1994). The nonlinear dynamics of speech categorization. Journal of Experimental Psychology: Human Perception and Performance, 20(1), 3–16.
			* Wilensky, U., & Resnick, M. (1999). Springer Thinking in Levels: A Dynamic Systems Approach to Making Sense of the World Thinking in Levels: A Dynamic Systems Approach to Making Sense of the World. Source: Journal of Science Education and Technology Journal of Science Education and Technology, 8(1), 3–19.

Wehner am 27. August 2018 um 07:47 Uhr

2018-08-27T07:47:03Z

← Nächstältere Version		Version vom 27. August 2018, 09:47 Uhr
Zeile 1:		Zeile 1:
			'''Einführung in die Methoden & Versuchsplanung'''

	* Bortz, J., Döring, N. (2006) Forschungsmethoden und Evaluation. Berlin: Springer		* Bortz, J., Döring, N. (2006) Forschungsmethoden und Evaluation. Berlin: Springer
	* Goodwin, C. J. (2009) Research in Psychology. Hoboken NJ: Wiley		* Goodwin, C. J. (2009) Research in Psychology. Hoboken NJ: Wiley
Zeile 10:		Zeile 12:
	* Whitley, B.E., Kite, M.E. (2013) Principles of Research in Behavioral Science. New York: Routledge		* Whitley, B.E., Kite, M.E. (2013) Principles of Research in Behavioral Science. New York: Routledge
	* Walach, H. (2013) Psychologie: Wissenschaftstheorie, philosophische Grundlagen und Geschichte. Stuttgart: Kohlhammer		* Walach, H. (2013) Psychologie: Wissenschaftstheorie, philosophische Grundlagen und Geschichte. Stuttgart: Kohlhammer


			''' Kognitive Modellierung'''