Psychonomic Bulletin & Review

, Volume 22, Issue 2, pp 328–348 | Cite as

Explaining individual differences in cognitive processes underlying hindsight bias

  • Alisha Coolin
  • Edgar Erdfelder
  • Daniel M. Bernstein
  • Allen E. Thornton
  • Wendy Loken ThorntonEmail author
Theoretical Review


After learning an event’s outcome, people’s recollection of their former prediction of that event typically shifts toward the actual outcome. Erdfelder and Buchner (Journal of Experimental Psychology: Learning, Memory, and Cognition, 24, 387–414, 1998) developed a multinomial processing tree (MPT) model to identify the underlying processes contributing to this hindsight bias (HB) phenomenon. More recent applications of this model have revealed that, in comparison to younger adults, older adults are more susceptible to two underlying HB processes: recollection bias and reconstruction bias. However, the impact of cognitive functioning on these processes remains unclear. In this article, we extend the MPT model for HB by incorporating individual variation in cognitive functioning into the estimation of the model’s core parameters in older and younger adults. In older adults, our findings revealed that (1) better episodic memory was associated with higher recollection ability in the absence of outcome knowledge, (2) better episodic memory and inhibitory control and higher working memory capacity were associated with higher recollection ability in the presence of outcome knowledge, and (3) better inhibitory control was associated with less reconstruction bias. Although the pattern of effects was similar in younger adults, the cognitive covariates did not significantly predict the underlying HB processes in this age group. In sum, we present a novel approach to modeling individual variability in MPT models. We applied this approach to the HB paradigm to identify the cognitive mechanisms contributing to the underlying HB processes. Our results show that working memory capacity and inhibitory control, respectively, drive individual differences in recollection bias and reconstruction bias, particularly in older adults.


Multinomial processing tree models Hindsight bias Individual differences Cognitive functioning 


Author note

This research was supported by the Social Sciences and Humanities Research Council (SSHRC), Canada Research Chairs, the Natural Science and Engineering Research Council (NSERC), and the German Research Foundation (GRF, Er 224/2-2)..


  1. Akaike, H. (1974). A new look at the statistical model identification. IEEE Transactions on Automatic Control, AC-19, 716–723. doi: 10.1109/TAC.1974.1100705 CrossRefGoogle Scholar
  2. Akaike, H. (1978). A new look at the Bayes procedure. Biometrika, 65, 53–59.CrossRefGoogle Scholar
  3. Ansari, A., Vanhuele, M., & Zemborain, M. (2008). Heterogeneous multinomial processing tree models. Unpublished manuscript. Columbia University, New York.Google Scholar
  4. Arkes, H. R., Wortman, R. L., Saville, P. D., & Harkness, A. R. (1981). Hindsight bias among physicians weighing the likelihood of diagnoses. Journal of Applied Psychology, 66, 252–254.CrossRefPubMedGoogle Scholar
  5. Ashby, F. G., Prinzmetal, W., Ivry, R., & Maddox, W. T. (1996). A formal theory of feature binding in object perception. Psychological Review, 103, 165–192. doi: 10.1037/0033-295X.103.1.165 CrossRefPubMedGoogle Scholar
  6. Batchelder, W. H., & Riefer, D. M. (1999). Theoretical and empirical review of multinomial process tree models. Psychonomic Bulletin & Review, 6, 57–86. doi: 10.3758/BF03210812 CrossRefGoogle Scholar
  7. Bayen, U. J., Erdfelder, E., Bearden, J. N., & Lozito, J. P. (2006). The interplay of memory and judgment processes in effects of aging on hindsight bias. Journal of Experimental Psychology: Learning, Memory, and Cognition, 32, 1003–1018. doi: 10.1037/0278-7393.32.5.1003 PubMedGoogle Scholar
  8. Bayen, U. J., Pohl, R. F., Erdfelder, E., & Auer, T.-S. (2007). Hindsight bias across the lifespan. Social Cognition, 25, 83–97.CrossRefGoogle Scholar
  9. Bernstein, D. M., Erdfelder, E., Meltzoff, A. N., Perria, W., & Loftus, G. R. (2011). Hindsight bias from 3 to 95 years of age. Journal of Experimental Psychology: Learning, Memory, and Cognition, 37, 378–391.PubMedCentralPubMedGoogle Scholar
  10. Blank, H., & Nestler, S. (2007). Cognitive process models of hindsight bias. Social Cognition, 25, 132–146.CrossRefGoogle Scholar
  11. Burnham, K. P., & Anderson, D. R. (2002). Model selection and multimodel inference: A practical information-theoretic approach. New York, NY: Springer.Google Scholar
  12. Calvillo, D. P. (2012). Working memory and the memory distortion component of hindsight bias. Memory, 20, 891–898. doi: 10.1080/09658211.2012.706309 CrossRefPubMedGoogle Scholar
  13. Christensen, H., Mackinnon, A., Jorm, A. F., Henderson, A. S., Scott, L. R., & Korten, A. E. (1994). Age differences and interindividual variation in cognition in community-dwelling elderly. Psychology and Aging, 9, 381–390.CrossRefPubMedGoogle Scholar
  14. Christensen-Szalanski, J. J. J., & Willham, C. F. (1991). The hindsight bias: A meta-analysis. Organizational Behavior and Human Decision Processes, 48, 147–168.CrossRefGoogle Scholar
  15. Cohen, J. (1988). Statistical power analysis for the behavioral sciences (2nd ed.). Hillsdale, NJ: Erlbaum.Google Scholar
  16. Coolin, A., Bernstein, D. M., Thornton, A. E., & Thornton, W. L. (2014). Age differences in hindsight bias: The role of episodic memory and inhibition. Experimental Aging Research, 40, 357–374.CrossRefPubMedGoogle Scholar
  17. Dehn, D. M., & Erdfelder, E. (1998). What kind of bias is hindsight bias? Psychological Research, 61, 135–146.CrossRefGoogle Scholar
  18. Delis, D. C., Kaplan, E., & Kramer, J. H. (2001). Delis–Kaplan executive function system. San Antonio, TX: Psychological Corp.Google Scholar
  19. Delis, D. C., Kramer, J. H., Kaplan, E., & Ober, B. A. (2000). California Verbal Learning Test–2nd ed. (CVLT-II). San Antonio, TX: Psychological Corp.Google Scholar
  20. Dunn, L. M., & Dunn, L. M. (1997). Peabody Picture Vocabulary Test 3rd ed. (PPVT-III). Circle Pines, MN: American Guidance Service.Google Scholar
  21. Edgington, E. S. (1995). Randomization tests (3rd ed.). New York, NY: Marcel Dekker.Google Scholar
  22. Efron, B., & Tibshirani, R. J. (1993). An introduction to the bootstrap. New York, NY: Chapman & Hall.CrossRefGoogle Scholar
  23. Erdfelder, E., Auer, T.-S., Hilbig, B. E., Aßfalg, A., Moshagen, M., & Nadarevic, L. (2009). Multinomial processing tree models: A review of the literature. Journal of Psychology, 217, 108–124.Google Scholar
  24. Erdfelder, E., Brandt, M., & Bröder, A. (2007). Recollection biases in hindsight judgments. Social Cognition, 25, 114–131.CrossRefGoogle Scholar
  25. Erdfelder, E., & Buchner, A. (1998). Decomposing the hindsight bias: A multinomial processing tree model for separating recollection and reconstruction in hindsight. Journal of Experimental Psychology: Learning, Memory, and Cognition, 24, 387–414. doi: 10.1037/0278-7393.24.2.387 Google Scholar
  26. Faul, F., Erdfelder, E., Lang, A.-G., & Buchner, A. (2007). G*Power 3: A flexible statistical power analysis program for the social, behavioral, and biomedical sciences. Behavior Research Methods, 39, 175–191. doi: 10.3758/BF03193146 CrossRefPubMedGoogle Scholar
  27. Fischhoff, B. (1975). Hindsight ≠ foresight: The effect of outcome knowledge on judgment under uncertainty. Journal of Experimental Psychology: Human Perception and Performance, 1, 288–299.Google Scholar
  28. Folstein, M. F., Folstein, S. E., & McHugh, P. R. (1975). “Mini Mental State”: A practical method for grading the cognitive state of patients for the clinician. Journal of Psychiatric Research, 12, 189–198. doi: 10.1016/0022-3956(75)90026-6 CrossRefPubMedGoogle Scholar
  29. Groß, J., & Bayen, U. J. (in press). Hindsight bias in younger and older adults: The role of access control. Neuropsychology, Development, and Cognition. Google Scholar
  30. Guilbault, R. L., Bryant, F. B., Brockway, J. H., & Posavac, E. J. (2004). A meta-analysis of research on hindsight bias. Basic and Applied Social Psychology, 26, 103–117.CrossRefGoogle Scholar
  31. Hardt, O., & Pohl, R. F. (2003). Hindsight bias as a function of anchor distance and anchor plausibility. Memory, 11, 397–394.CrossRefGoogle Scholar
  32. Harley, E. M. (2007). Hindsight bias in legal decision making. Social Cognition, 25, 48–63.CrossRefGoogle Scholar
  33. Hasher, L., & Zacks, R. T. (1988). Working memory, comprehension, and aging: A review and a new view. In G. H. Bower (Ed.), The psychology of learning and motivation: Advances in research and theory (Vol. 22, pp. 193–225). San Diego, CA: Academic.Google Scholar
  34. Hawkins, S. A., & Hastie, R. (1990). Hindsight: Biased judgments of past events after the outcomes are known. Psychological Bulletin, 107, 311–327. doi: 10.1037/0033-2909.107.3.311 CrossRefGoogle Scholar
  35. Hedden, T., & Gabrieli, J. D. E. (2004). Insights into the ageing mind: A view from cognitive neuroscience. Natures Review Neuroscience, 5, 87–96.CrossRefGoogle Scholar
  36. Hell, W., Gigerenzer, G., Gauggel, S., Mall, M., & Müller, M. (1988). Hindsight bias: An interaction of automatic and motivational factors? Memory & Cognition, 16, 533–538. doi: 10.3758/BF03197054 CrossRefGoogle Scholar
  37. Hoffrage, U., Hertwig, R., & Gigerenzer, G. (2000). Hindsight bias: A by-product of knowledge updating? Journal of Experimental Psychology: Learning, Memory, and Cognition, 26, 566–581.PubMedGoogle Scholar
  38. Hu, X., & Batchelder, W. H. (1994). The statistical analysis of engineering processing tree models with the EM algorithm. Psychometrika, 59, 21–47. doi: 10.1007/BF02294263 CrossRefGoogle Scholar
  39. Klauer, K. C. (2006). Hierarchical multinomial processing tree models: A latent-class approach. Psychometrika, 71, 7–31.CrossRefGoogle Scholar
  40. Klauer, K. C. (2010). Hierarchical multinomial processing tree models: A latent-trait approach. Psychometrika, 75, 70–98. doi: 10.1007/s11336-009-9141-0 CrossRefGoogle Scholar
  41. Klauer, K. C., Stahl, C., & Erdfelder, E. (2007). The abstract selection task: New data and an almost comprehensive model. Journal of Experimental Psychology: Learning, Memory, and Cognition, 33, 680–703.PubMedGoogle Scholar
  42. Leary, M. R. (1981). The distorted nature of hindsight. Journal of Social Psychology, 115, 25–29.CrossRefGoogle Scholar
  43. Lustig, C., Hasher, L., & Zacks, R. T. (2007). Inhibitory deficit theory: Recent developments in a “new view”. In C. M. MacLeod & D. S. Gorfein (Eds.), Inhibition in cognition (pp. 145–162). Washington, DC: American Psychological Association.CrossRefGoogle Scholar
  44. McCloskey, M., & Zaragoza, M. (1985). Misleading postevent information and memory for events: Arguments and evidence against the memory impairment hypothesis. Journal of Experimental Psychology: General, 114, 1–16. doi: 10.1037/0096-3445.114.1.1 CrossRefGoogle Scholar
  45. Myung, I. J. (2000). The importance of complexity in model selection. Journal of Mathematical Psychology, 44, 190–204. doi: 10.1006/jmps.1999.1283 CrossRefPubMedGoogle Scholar
  46. Myung, I. J., & Pitt, M. A. (1997). Applying Occam’s razor in modeling cognition: A Bayesian approach. Psychonomic Bulletin & Review, 4, 79–95. doi: 10.3758/BF03210778 CrossRefGoogle Scholar
  47. Nestler, S., Blank, H., & Egloff, B. (2010). Hindsight ≠ hindsight: Experimentally induced dissociation between hindsight components. Journal of Experimental Psychology: Learning, Memory, and Cognition, 36, 1399–1413.PubMedGoogle Scholar
  48. Nestler, S., Blank, H., & von Collani, G. (2008). Hindsight bias doesn’t always come easy: Causal models, cognitive effort, and creeping determinism. Journal of Experimental Psychology: Learning, Memory, and Cognition, 34, 1043–1054.PubMedGoogle Scholar
  49. Newton, J. M., & Wickens, D. D. (1956). Retroactive inhibition as a function of the temporal position of interpolated learning. Journal of Experimental Psychology, 51, 149–154.CrossRefPubMedGoogle Scholar
  50. Peters, E., Hess, T. M., Vastfjall, 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 Sciences, 2, 1–23.CrossRefGoogle Scholar
  51. Pezzo, M. V., & Pezzo, S. P. (2007). Making sense of failure: A motivated model of hindsight bias. Social Cognition, 25, 147–164.CrossRefGoogle Scholar
  52. Pohl, R. F. (2004). Hindsight bias. In R. F. Pohl (Ed.), Cognitive illusions: A handbook on fallacies and biases in thinking, judgement, and memory (pp. 363–378). Hove, UK: Psychology Press.Google Scholar
  53. Pohl, R. F. (2007). Ways to assess hindsight bias. Social Cognition, 25, 14–31.CrossRefGoogle Scholar
  54. Pohl, R. F., Bayen, U. J., & Martin, C. (2010). A multiprocess account of hindsight bias in children. Developmental Psychology, 46, 1268–1282.CrossRefPubMedGoogle Scholar
  55. Pohl, R. F., Eisenhauer, M., & Hardt, O. (2003). SARA: A cognitive process model to simulate the anchoring effect and hindsight bias. Memory, 11, 337–356.CrossRefPubMedGoogle Scholar
  56. Raz, N., Ghisletta, P., Rodrigue, K. M., Kennedy, K., & Lindenberger, U. (2010). Trajectories of brain aging in middle-aged and older adults: Regional and individual differences. NeuroImage, 51, 501–511.CrossRefPubMedCentralPubMedGoogle Scholar
  57. Riddle, D. R. (2007). Brain aging: Models, methods, and mechanisms. Boca Raton, FL: CRC Press.CrossRefGoogle Scholar
  58. Salthouse, T. A. (2000). Aging and measures of processing speed. Biological Psychology, 54, 35–54.CrossRefPubMedGoogle Scholar
  59. Schwarz, S., & Stahlberg, D. (2003). Strength of hindsight bias as a consequence of metacognitions. Memory, 11, 395–410.CrossRefPubMedGoogle Scholar
  60. Smith, J. B., & Batchelder, W. H. (2008). Assessing individual differences in categorical data. Psychonomic Bulletin & Review, 15, 713–731. doi: 10.3758/PBR.15.4.713 CrossRefGoogle Scholar
  61. Smith, J. B., & Batchelder, W. H. (2010). Beta-MPT: Multinomial processing tree models for addressing individual differences. Journal of Mathematical Psychology, 54, 167–183.CrossRefGoogle Scholar
  62. Stahl, C., & Klauer, K. C. (2007). HMMTree: A computer program for latent class hierarchical multinomial processing tree models. Behavior Research Methods, 39, 267–273. doi: 10.3758/BF03193157 CrossRefPubMedGoogle Scholar
  63. Stahlberg, D., & Maass, A. (1998). Hindsight bias: Impaired memory or biased reconstruction? In W. Stroebe & M. Hewstone (Eds.), European Review of Social Psychology (Vol. 8, pp. 105–132). London, UK: Wiley.Google Scholar
  64. Wagenmakers, E.-J., & Farrell, S. (2004). AIC model selection using Akaike weights. Psychonomic Bulletin & Review, 11, 192–196. doi: 10.3758/BF03206482 CrossRefGoogle Scholar
  65. Wechsler, D. (1997). Wechsler Adult Intelligence Scale–3rd ed. (WAIS-III). New York, NY: Psychological Corp.Google Scholar
  66. Winman, A., Juslin, P., & Björkman, M. (1998). The confidence–hindsight mirror effect in judgment: An accuracy-assessment model for the knew-it-all-along phenomenon. Journal of Experimental Psychology: Learning, Memory, and Cognition, 24, 415–431. doi: 10.1037/0278-7393.24.2.415 Google Scholar
  67. Zelazo, P. D., Craik, F. I. M., & Booth, L. (2004). Executive function across the life span. Acta Psychologica, 115, 167–183. doi: 10.1016/j.actpsy.2003.12.005 CrossRefPubMedGoogle Scholar

Copyright information

© Psychonomic Society, Inc. 2014

Authors and Affiliations

  • Alisha Coolin
    • 1
  • Edgar Erdfelder
    • 2
  • Daniel M. Bernstein
    • 3
  • Allen E. Thornton
    • 1
    • 4
  • Wendy Loken Thornton
    • 1
    Email author
  1. 1.Department of PsychologySimon Fraser UniversityBurnabyCanada
  2. 2.Department of PsychologyUniversity of MannheimMannheimGermany
  3. 3.Department of PsychologyKwantlen Polytechnic UniversitySurreyCanada
  4. 4.BC Mental Health and Addictions Research InstituteBurnabyCanada

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