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Cognitive Aging and Tests of Rationality

Published online by Cambridge University Press:  23 December 2019

Sanghyuk Park ,
Clintin P. Davis-Stober Open the ORCID record for Clintin P. Davis-Stober [Opens in a new window] ,
Hope K. Snyder ,
William Messner  and
Michel Regenwetter Open the ORCID record for Michel Regenwetter [Opens in a new window]
Sanghyuk Park
Affiliation:
University of Missouri Columbia (USA)
Clintin P. Davis-Stober*
Affiliation:
University of Missouri Columbia (USA)
Hope K. Snyder
Affiliation:
University of Missouri Columbia (USA)
William Messner
Affiliation:
The Lubrizol Corporation (USA)
Michel Regenwetter*
Affiliation:
University of Illinois at Urbana-Champaign (USA)
*
*Correspondence concerning this article should be addressed to Clintin Davis-Stober. University of Missouri Columbia. Department of Psychological Sciences. 65211 Columbia Missouri (USA). E-mail: (stoberc@missouri.edu).
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Abstract

We investigated whether older adults are more likely than younger adults to violate a foundational property of rational decision making, the axiom of transitive preference. Our experiment consisted of two groups, older (ages 60-75; 21 participants) and younger (ages 18-30; 20 participants) adults. We used Bayesian model selection to investigate whether individuals were better described via (transitive) weak order-based decision strategies or (possibly intransitive) lexicographic semiorder decision strategies. We found weak evidence for the hypothesis that older adults violate transitivity at a higher rate than younger adults. At the same time, a hierarchical Bayesian analysis suggests that, in this study, the distribution of decision strategies across individuals is similar for both older and younger adults.

Keywords

cognitive agingrational decision makingtransitivity of preferenceprobabilistic choicerandom preference
Type
Research Article
Information
The Spanish Journal of Psychology , Volume 22 , 2019 , E57
Copyright
Copyright © Universidad Complutense de Madrid and Colegio Oficial de Psicólogos de Madrid 2019 

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Footnotes

This paper grew out of an invited talk given at the VII Advanced International Seminar Mathematical Models of Decision Making Processes: State of the Art and Challenges held at the School of Psychology, Universidad Complutense de Madrid (Spain) in October 2018 (http://eventos.ucm.es/go/DecisionMakingModels). This paper was supported by: Air Force Office of Scientific Research grant FA9550-05-1-0356 (PI: M. Regenwetter); Pilot Grant Program of the University of Illinois Center for Healthy Minds # PHS 1 P30 AG023101 (funded by the National Institutes of Aging); National Science Foundation (NSF) SES # 08-20009 (PI: M. Regenwetter), SES # 10-62045 (PI: M. Regenwetter), SES # 14-59699 (PI: M. Regenwetter) and SES # 14-59866 (PI: Clintin P. Davis-Stober); National Institutes of Health (K25AA024182, PI: C. Davis-Stober). This project was approved by University of Illinois at Urbana-Champaign Institutional Review Board, project number 07762. Any opinions, findings, conclusions, or recommendations expressed in this publication are those of the authors and do not necessarily reflect the views of their funding agencies or universities.

How to cite this article:

Park, S., Davis-Stober, C. P., Synder, H., Messner, W., & Regenwetter, M. (2019). Cognitive aging and tests of rationality. The Spanish Journal of Psychology, 22. e57. Doi:10.1017/sjp.2019.52

References

Anand, P. (1993). The philosophy of intransitive preference. The Economic Journal, 103(417), 337–346. http://doi.org/10.2307/2234772CrossRefGoogle Scholar
Ballhausen, N., Schnitzspahn, K. M., Horn, S. S., & Kliegel, M. (2017). The interplay of intention maintenance and cue monitoring in younger and older adults prospective memory. Memory & Cognition, 45(7), 1113–1125. http://doi.org/10.3758/s13421-017-0720-5CrossRefGoogle ScholarPubMed
Berg, C. A., Meegan, S. P., & Klaczynski, P. (1999). Age and experiential differences in strategy generation and information requests for solving everyday problems. International Journal of Behavioral Development, 23(3), 615–639. http://doi.org/10.1080/016502599383720CrossRefGoogle Scholar
Bernardo, J. M. (1996). The concept of exchangeability and its applications. Far East Journal of Mathematical Sciences, 4, 111–122.Google Scholar
Besedeš, T., Deck, C., Sarangi, S., & Shor, M. (2012). Age effects and heuristics in decision making. Review of Economics and Statistics, 94(2), 580–595. http://doi.org/10.1162/REST_a_00174CrossRefGoogle ScholarPubMed
Blei, D. M., Ng, A. Y., & Jordan, M. I. (2003). Latent Dirichlet allocation. Journal of Machine Learning Research, 3 , 993–1022.Google Scholar
Brandstätter, E., Gigerenzer, G., & Hertwig, R. (2006). The priority heuristic: Making choices without trade-offs. Psychological Review, 113(2), 409–432. http://doi.org/10.1037/0033-295X.113.2.409CrossRefGoogle ScholarPubMed
Cavagnaro, D. R., & Davis-Stober, C. P. (2014). Transitive in our preferences, but transitive in different ways: An analysis of choice variability. Decision, 1(2), 102–122. http://doi.org/10.1037/dec0000011CrossRefGoogle Scholar
Cavagnaro, D. R., & Davis-Stober, C. P. (2018). A model based test for treatment effects with probabilistic classifications. Psychological Methods, 23(4), 672–689. http://doi.org/10.1037/met0000173CrossRefGoogle Scholar
Chung, H.-K., Tymula, A., & Glimcher, P. (2017). The reduction of ventrolateral prefrontal cortex gray matter volume correlates with loss of economic rationality in aging. Journal of Neuroscience, 37(49), 12068–12077. http://doi.org/10.1523/JNEUROSCI.1171-17.2017CrossRefGoogle Scholar
Dai, J. (2017). Are intertemporal preferences transitive? A Bayesian analysis of repeated individual intertemporal choices. Decision, 4 (1), 1–24. http://doi.org/10.1037/dec0000054CrossRefGoogle Scholar
Davidson, D., & Marschak, J. (1959). Experimental tests of a stochastic decision theory. Measurement: Definitions and Theories, 233–269.Google Scholar
Davis-Stober, C. P. (2010). A bijection between a set of lexicographic semiorders and pairs of non-crossing dyck paths. Journal of Mathematical Psychology, 54(6), 471–474. http://doi.org/10.1016/j.jmp.2010.09.001CrossRefGoogle Scholar
Davis-Stober, C. P. (2012). A lexicographic semiorder polytope and probabilistic representations of choice. Journal of Mathematical Psychology, 56(2), 86–94. http://doi.org/10.1016/j.jmp.2012.01.003CrossRefGoogle Scholar
Davis-Stober, C. P., Brown, N., & Cavagnaro, D. R. (2015). Individual differences in the algebraic structure of preferences. Journal of Mathematical Psychology, 66, 70–82. http://doi.org/10.1016/j.jmp.2014.12.003CrossRefGoogle Scholar
Davis-Stober, C. P., McCarthy, D. M., Cavagnaro, D. R., Price, M., Brown, N., & Park, S. (2019). Is cognitive impairment related to violations of rationality? A laboratory alcohol intoxication study testing transitivity of preference. Decision, 6, 134–144. http://doi.org/10.1037/dec0000093CrossRefGoogle Scholar
Denburg, N. L., Cole, C. A., Hernandez, M., Yamada, T. H., Tranel, D., Bechara, A., & Wallace, R. B. (2007). The orbitofrontal cortex, real-world decision making, and normal aging. Annals of the New York Academy of Sciences, 1121(1), 480–498. http://doi.org/10.1196/annals.1401.031CrossRefGoogle ScholarPubMed
Estes, W. K. (1956). The problem of inference from curves based on group data. Psychological Bulletin, 53(2), 134–140. http://doi.org/10.1037/h0045156CrossRefGoogle ScholarPubMed
Finucane, M. L., Slovic, P., Hibbard, J. H., Peters, E., Mertz, C. K., & MacGregor, D. G. (2002). Aging and decision-making competence: An analysis of comprehension and consistency skills in older versus younger adults considering health-plan options. Journal of Behavioral Decision Making, 15(2), 141–164. http://doi.org/10.1002/bdm.407CrossRefGoogle Scholar
Frey, R., Mata, R., & Hertwig, R. (2015). The role of cognitive abilities in decisions from experience: Age differences emerge as a function of choice set size. Cognition, 142, 60–80. http://doi.org/10.1016/j.cognition.2015.05.004CrossRefGoogle ScholarPubMed
Gigerenzer, G., Todd, P. M., ABC Research Group (1999). Simple heuristics that make us smart. New York, NY: Oxford University Press.Google Scholar
He, W., Goodking, D., & Kowal, P. (2016). An aging world: 2015. International Populations Report . Washington, DC: United States Census Bureau, U.S. Department of Commerce Economics and Statistics Administration, U.S. Department of Health and Human Services.Google Scholar
Heck, D. W., & Davis-Stober, C. P. (2019). Multinomial models with linear inequality constraints: Overview and improvements of computational methods for Bayesian inference. Journal of Mathematical Psychology, 91, 70–87. http://doi.org/10.1016/j.jmp.2019.03.004CrossRefGoogle ScholarPubMed
Hertzog, C., Cooper, B. P., & Fisk, A. D. (1996). Aging and individual differences in the development of skilled memory search performance. Psychology and Aging, 11(3), 497–520. http://doi.org/10.1037/0882-7974.11.3.497CrossRefGoogle ScholarPubMed
Hey, J. D. (2005). Why we should not be silent about noise. Experimental Economics, 8(4), 325–345. https://doi.org/10.1007/s10683-005-5373-8CrossRefGoogle Scholar
Jeffreys, H. (1961). The Theory of Probability (3rd Ed). Oxford, UK: Oxford University Press.Google Scholar
Klugkist, I., & Hoijtink, H. (2007). The Bayes factor for inequality and about equality constrained models. Computational Statistics & Data Analysis, 51(12), 6367–6379. http://doi.org/10.1016/j.csda.2007.01.024CrossRefGoogle Scholar
Luce, R. D. (2000). Utility of gains and losses: Measurement-theoretical and experimental approaches. London, UK: Lawrence Erlbaum Associates, Inc.Google Scholar
Marley, A. A. J., & Regenwetter, M. (2017). Choice, preference, and utility: Probabilistic and deterministic representations. In Batchelder, W., Colonius, H., Dzhafarov, E., & Myung, J. (Eds.), New handbook of mathematical psychology (pp. 374–453). Cambridge, UK: Cambridge University Press. http://doi.org/10.1017/9781139245913.008Google Scholar
Mata, R., Schooler, L. J., & Rieskamp, J. (2007). The aging decision maker: Cognitive aging and the adaptive selection of decision strategies. Psychology and Aging, 22(4), 796–810. http://doi.org/10.1037/0882-7974.22.4.796CrossRefGoogle ScholarPubMed
McGillivray, S., Friedman, M. C., & Castel, A. D. (2012). Impact of aging on thinking. The Oxford handbook of thinking and reasoning, 650–672. http://doi.org/10.1093/oxfordhb/9780199734689.013.0033Google Scholar
Ortman, J. M., Velkoff, V. A., & Hogan, H. (2014). An aging nation: The older population in the United States. Population estimates and projections . Retrieved from United States Census Bureau website: https://www.census.gov/prod/2014pubs/p25-1140.pdfGoogle Scholar
Peters, E., Hess, T. M., Västfjäll, D., & Auman, C. (2007). Adult age differences in dual information processes: Implications for the role of affective and deliberative processes in older adults decision making. Perspectives on Psychological Science, 2, 1–23. http://doi.org/10.1111/j.1745-6916.2007.00025.xCrossRefGoogle ScholarPubMed
Pirlot, M., & Vincke, P. (1997). Semiorders: Properties, representations, applications. Dordrecht, the Netherlands: Springer Science & Business Media.CrossRefGoogle Scholar
Queen, T. L., Hess, T. M., Ennis, G. E., Dowd, K., & Grühn, D. (2012). Information search and decision making: Effects of age and complexity on strategy use. Psychology and Aging, 27 (4), 817–824. http://doi.org/10.1037/a0028744CrossRefGoogle ScholarPubMed
Regenwetter, M., Cavagnaro, D. R., Popova, A., Guo, Y., Zwilling, C., Lim, S. H., … Stevens, J. R. (2018). Heterogeneity and parsimony in intertemporal choice. Decision, 5(2), 63–94. http://doi.org/10.1037/dec0000069CrossRefGoogle Scholar
Regenwetter, M., & Cavagnaro, D. R. (2018). Tutorial on removing the shackles of regression analysis: How to stay true to your theory of binary response probabilities. Psychological Methods, 24(2), 135–152. http://doi.org/10.1037/met0000196CrossRefGoogle ScholarPubMed
Regenwetter, M., Dana, J., & Davis-Stober, C. P. (2011). Transitivity of preferences. Psychological Review, 118(1), 42–56. http://doi.org/10.1037/a0021150CrossRefGoogle ScholarPubMed
Regenwetter, M., Dana, J., Davis-Stober, C. P., & Guo, Y. (2011). Parsimonious testing of transitive or intransitive preferences: Reply to Birnbaum (2011). Psychological Review, 118, 684–688. http://doi.org/10.1037/a0025291CrossRefGoogle Scholar
Regenwetter, M., & Davis-Stober, C. P. (2012). Behavioral variability of choices versus structural inconsistency of preferences. Psychological Review, 119(2), 408–416. http://doi.org/10.1037/a0027372CrossRefGoogle ScholarPubMed
Regenwetter, M., & Davis-Stober, C. P. (2018). The role of independence and stationarity in probabilistic models of binary choice. Journal of Behavioral Decision Making, 31(1), 100–114. http://doi.org/10.1002/bdm.2037CrossRefGoogle ScholarPubMed
Regenwetter, M., Davis-Stober, C. P., Lim, S. H., Guo, Y., Popova, A., Zwilling, C., … Messner, W. (2014). QTest: Quantitative testing of theories of binary choice. Decision, 1(1), 2–34. http://doi.org/10.1037/dec0000007CrossRefGoogle ScholarPubMed
Regenwetter, M., & Robinson, M. M. (2017). The construct–behavior gap in behavioral decision research: A challenge beyond replicability. Psychological Review, 124(5), 533–550. http://doi.org/10.1037/rev0000067CrossRefGoogle ScholarPubMed
Rieskamp, J., & Hoffrage, U. (2008). Inferences under time pressure: How opportunity costs affect strategy selection. Acta Psychologica, 127(2), 258–276. http://doi.org/10.1016/j.actpsy.2007.05.004CrossRefGoogle ScholarPubMed
Silvapulle, M. J., & Sen, P. K. (2011). Constrained statistical inference: Order, inequality, and shape constraints. Hoboken, NJ: John Wiley & Sons.Google Scholar
Tversky, A. (1969) Intransitivity of preferences. Psychological Review, 76(1), 31–48. http://doi.org/10.1037/h0026750CrossRefGoogle Scholar
Tymula, A., Belmaker, L. A. R., Ruderman, L., Glimcher, P. W., & Levy, I. (2013). Like cognitive function, decision making across the life span shows profound age-related changes. Proceedings of the National Academy of Sciences, 110(42), 17143–17148. http://doi.org/10.1073/pnas.1309909110CrossRefGoogle ScholarPubMed
Zwilling, C., Cavagnaro, D., Regenwetter, M., Lim, S. H., Fields, B., & Zhang, Y. (2019). QTest 2.1: Quantitative testing of theories of binary choice using Bayesian inference. Journal of Mathematical Psychology, 91, 176–194. http://doi.org/10.1016/j.jmp.2019.05.002CrossRefGoogle Scholar