A multinomial model of applying recognition to judge between multiple alternatives
Beaman, P. (2012) A multinomial model of applying recognition to judge between multiple alternatives. In: 11th International Conference on Cognitive Modeling, 13-15 April 2012, Berlin, pp. 25-30.
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Proponents of the “fast and frugal” approach to decision-making suggest that inferential judgments are best made on the basis of limited information. For example, if only one of two cities is recognized and the task is to judge which city has the larger population, the recognition heuristic states that the recognized city should be selected. In preference choices with >2 options, it is also standard to assume that a “consideration set”, based upon some simple criterion, is established to reduce the options available. A multinomial processing tree model is outlined which provides the basis for estimating the extent to which recognition is used as a criterion in establishing a consideration set for inferential judgments.
Batchelder, W. H., & Riefer, D. M. (1999). Theoretical and empirical review of multinomial process tree modeling. Psychonomic Bulletin & Review, 6, 57-86. Beaman, C. P., Smith, P. T., Frosch, C. A., & McCloy, R. (2010). Less-is-more effects without the recognition heuristic. Judgment & Decision-Making, 5, 258-271. Frosch, C., Beaman, C. P., & McCloy, R. (2007). A little learning is a dangerous thing: An experimental demonstration of ignorance-driven inference. Quarterly Journal of Experimental Psychology, 60, 1329-1336 Gigerenzer, G., & Goldstein, D. G. (1996). Reasoning the fast and frugal way: Models of bounded rationality. Psychological Review, 103, 650-669. Gigerenzer, G., Hertwig, R., & Pachur, T. (2011). Heuristics: The foundations of adaptive behavior. Oxford: OUP. Goldstein, D., & Gigerenzer, G. (2002). Models of ecological rationality: The recognition heuristic. Psychological Review, 103, 650-669. Hilbig, B. E. (2010). Precise models deserve precise measures: a methodological dissection. Judgment and Decision Making, 5, 272-284 Hilbig, B. E., Erdfelder, E., & Pohl, R. F. (2010). Onereason decision-making unveiled: A measurement model of the recognition heuristic. Journal of Experimental Psychology: Learning, Memory & Cognition 36, 123-134 Hilbig, B. E. & Pohl, R. F. (2008). Recognizing users of the recognition heuristic. Experimental Psychology, 55, 394- 401 Hilbig, B. E., Pohl, R. F. & Bröder, A. (2009). Criterion knowledge: A moderator of using the recognition heuristic? Journal of Behavioral Decision Making, 22, 510-522 Hilbig, B. E., & Richter, T. (2011). Homo heuristicus outnumbered: Comment on Gigerenzer and Brighton (2009). Topics in Cognitive Science, 3, 187-196 Howard, J. A. (1963). Consumer Behaviour: Application of theory. New York: McGraw-Hill. Moshagen, M. (2010). multiTree: A computer program for the analysis of multinomial processing tree models. Behavior Research Methods, 42, 42-54. Marewski, J. N., Gaissmaier, W., Schooler, L. J., Goldstein, D. G., & Gigerenzer, G. (2010). From recognition to decisions: Extending and testing recognition-based models for multi-alternative inference. Psychonomic Bulletin & Review, 17, 287-309. Marewski, J. N., & Mehlhorn, K. (2011). Using the ACT-R architecture to specify 39 quantitative process models of decision making. Judgment and Decision Making, 6, 439- 519 McCloy, R., Beaman, C. P., & Smith, P. T. (2008). The relative success of recognition-based inference in multichoice decisions. Cognitive Science, 32, 1037-1048 Pachur, T. & Hertwig, R. (2006). On the psychology of the recognition heuristic: Retrieval primacy as a key determinant of its use. Journal of Experimental Psychology: Learning, Memory & Cognition, 32, 983- 1002. Schooler, L. J., & Hertwig, R. (2005). How forgetting aids heuristic inference. Psychological Review, 112, 610-628. Smith, P. T., Beaman, C. P., & McCloy, R. (2011). The recognition heuristic and knowledge use. Poster presented to Subjective Probability, Utility & Decision-Making (SPUDM) 23, Kingston-upon-Thames, London. Sternberg, S. (1998). Discovering mental processing stages: The method of additive factors. In: D. Scarborough & S, Sternberg (Ed.s) An invitation to cognitive science, volume 4: Methods, models and conceptual issues. Cambridge, Ma.: MIT Press. Wright, P. & Barbour, T. (1977). Phased decision strategies: Sequels to initial screening. In: M. Starr & M. Zeleny (Ed.s) Multiple criteria decision making. Amsterdam: North Holland Publishing.
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