A Bayesian latent-mixture model analysis shows that informative samples reduce base-rate neglect

Decision

Volumn 2, Issue 4, 2015, Pages 306-318

  Hawkins, Guy E ^a   Hayes, Brett K ^a   Donkin, Chris ^a   Pasqualino, Martina ^a   Newell, Ben R ^a  

^a UNIVERSITY OF NEW SOUTH WALES   (Australia)

Author keywords

Base rate neglect; Bayesian analysis; Belief updating; Probabilistic judgment; Sequential sampling

Indexed keywords

EID: 84973134009     PISSN: 23259965     EISSN: 23259973     Source Type: Journal    
DOI: 10.1037/dec0000024     Document Type: Article

References (34)

1. Barbey, A. K., & Sloman, S. A. (2007). Base-rate respect: From ecological rationality to dual processes. Behavioral and Brain Sciences, 30, 241-254. http://dx.doi.org/10.1017/S0140525X07001653
2. Bar-Hillel, M. (1980). The base-rate fallacy in probability judgments. Acta Psychologica, 44, 211-233. http://dx.doi.org/10.1016/0001-6918(80) 90046-3
3. Bartlema, A., Lee, M., Wetzels, R., & Vanpaemel, W. (2014). A Bayesian hierarchical mixture approach to individual differences: Case studies in selective attention and representation in category learning. Journal of Mathematical Psychology, 59, 132-150. http://dx.doi.org/10.1016/j.jmp.2013.12.002
4. Cokely, E. T., Galesic, M., Schulz, E., Ghazal, S., & Garcia-Retamero, R. (2012). Measuring risk literacy: The Berlin Numeracy Test. Judgment and Decision Making, 7, 25-47
5. Cosmides, L., & Tooby, J. (1996). Are humans good intuitive statisticians after all? Rethinking some conclusions from the literature on judgment under uncertainty. Cognition, 58, 1-73. http://dx.doi.org/10.1016/0010-0277(95)00664-8
6. Eddy, D. M. (1982). Probabilistic reasoning in clinical medicine. In D. Kahneman, P. Slovic, & A. Tversky (Eds.), Judgment under uncertainty: Heuristics and biases (pp. 249-267). Cambridge, UK: Cambridge University Press. http://dx.doi.org/10.1017/CBO9780511809477.019
7. Evans, J. S. B. T., Handley, S. J., Perham, N., Over, D. E., & Thompson, V. A. (2000). Frequency versus probability formats in statistical word problems. Cognition, 77, 197-213. http://dx.doi.org/10.1016/S0010-0277(00)00098-6
8. Fantino, E., & Navarro, A. (2012). Description-experience gaps: Assessments in other choice paradigms. Journal of Behavioral Decision Making, 25, 303-314. http://dx.doi.org/10.1002/bdm.737
9. Fiedler, K. (2008). The ultimate sampling dilemma in experience-based decision making. Journal of Experimental Psychology: Learning, Memory, and Cognition, 34, 186-203. http://dx.doi.org/10.1037/0278-7393.34.1.186
10. Fiedler, K. (2012). Chapter one: Meta-cognitive myopia and the dilemmas of inductive-statistical inference. Psychology of Learning and Motivation, 57, 1-55. http://dx.doi.org/10.1016/B978-0-12-394293-7.00001-7
11. Fiedler, K., Brinkmann, B., Betsch, T., & Wild, B. (2000). A sampling approach to biases in conditional probability judgments: Beyond base-rate neglect and statistical format. Journal of Experimental Psychology: General, 129, 399-418. http://dx.doi.org/10.1037/0096-3445.129.3.399
12. Gigerenzer, G., & Gaissmaier, W. (2011). Heuristic decision making. Annual Review of Psychology, 62, 451-482. http://dx.doi.org/10.1146/annurevpsych-120709-145346
13. Gigerenzer, G., & Hoffrage, U. (1995). How to improve Bayesian reasoning without instruction: Frequency formats. Psychological Review, 102, 684-704. http://dx.doi.org/10.1037/0033-295X.102.4.684
14. Hogarth, R. M., Mukherjee, K., & Soyer, E. (2013). Assessing the chances of success: Naïve statistics versus kind experience. Journal of Experimental Psychology: Learning, Memory, and Cognition, 39, 14-32. http://dx.doi.org/10.1037/a0028522
15. Hogarth, R. M., & Soyer, E. (2011). Sequentially simulated outcomes: Kind experience versus nontransparent description. Journal of Experimental Psychology: General, 140, 434-463. http://dx.doi.org/10.1037/a0023265
16. Kahneman, D., & Tversky, A. (1972). Subjective probability: A judgment of representativeness. Cognitive Psychology, 3, 430-454. http://dx.doi.org/10.1016/0010-0285(72)90016-3
17. Kruschke, J. K. (2011). Doing Bayesian data analysis. Waltham, MA: Academic Press
18. Krynski, T. R., & Tenenbaum, J. B. (2007). The role of causality in judgment under uncertainty. Journal of Experimental Psychology: General, 136, 430-450. http://dx.doi.org/10.1037/0096-3445.136.3.430
19. Lantz, B. (2013). The impact of sample nonnormality on ANOVA and alternative methods. British Journal of Mathematical and Statistical Psychology, 66, 224-244. http://dx.doi.org/10.1111/j.2044-8317.2012.02047.x
20. Lejarraga, T. (2010). When experience is better than description: Time delays and complexity. Journal of Behavioral Decision Making, 23, 100-116. http://dx.doi.org/10.1002/bdm.666
21. McNair, S., & Feeney, A. (2014a). When does information about causal structure improve statistical reasoning? Quarterly Journal of Experimental Psychology: Human Experimental Psychology, 67, 625-645. http://dx.doi.org/10.1080/17470218.2013.821709
22. McNair, S., & Feeney, A. (2014b). Whose statistical reasoning is facilitated by a causal structure intervention? [Advance online publication]. Psychonomic Bulletin & Review. Advance online publication. http://dx.doi.org/10.3758/s13423-014-0645-y
23. Milligan, G. W. (1980). Factors that affect Type I and Type II error rates in the analysis of multidimensional contingency tables. Psychological Bulletin, 87, 238-244. http://dx.doi.org/10.1037/0033-2909.87.2.238
24. Morey, R. D., & Rouder, J. N. (2013). BayesFactor: Computation of Bayes factors for simple designs. [Online computer software manual]. Retrieved from http://CRAN.R-project.org/package=BayesFactor
25. Newell, B. R. (2013). Judgment under uncertainty. In D. Reisberg (Ed.), Oxford Handbook of Cognitive Psychology (pp. 602-615). New York, NY: Oxford University Press
26. Newell, B. R., Koehler, D. J., James, G., Rakow, T., & van Ravenzwaaij, D. (2013). Probability matching in risky choice: The interplay of feedback and strategy availability. Memory & Cognition, 41, 329-338. http://dx.doi.org/10.3758/s13421-012-0268-3
27. Newell, B. R., & Rakow, T. (2007). The role of experience in decisions from description. Psychonomic Bulletin & Review, 14, 1133-1139. http://dx.doi.org/10.3758/BF03193102
28. Rakow, T. R., Demes, K., & Newell, B. R. (2008). Biased samples not mode of presentation: Reexamining the apparent underweighting of rare events in experience-based choice. Organizational Behavior and Human Decision Processes, 106, 168-179. http://dx.doi.org/10.1016/j.obhdp.2008.02.001
29. Rouder, J. N., Speckman, P. L., Sun, D., Morey, R. D., & Iverson, G. (2009). Bayesian t tests for accepting and rejecting the null hypothesis. Psychonomic Bulletin & Review, 16, 225-237. http://dx.doi.org/10.3758/PBR.16.2.225
30. Sedlmeier, P. (1999). Improving statistical reasoning: Theoretical models and practical applications. Mahwah, NJ: Erlbaum
31. Tversky, A., & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185, 1124-1131. http://dx.doi.org/10.1126/science.185.4157.1124
32. Wagenmakers, E.-J. (2007). A practical solution to the pervasive problems of p values. Psychonomic Bulletin & Review, 14, 779-804. http://dx.doi.org/10.3758/BF03194105
33. Wagenmakers, E.-J., Lodewyckx, T., Kuriyal, H., & Grasman, R. (2010). Bayesian hypothesis testing for psychologists: A tutorial on the Savage-Dickey method. Cognitive Psychology, 60, 158-189. http://dx.doi.org/10.1016/j.cogpsych.2009.12.001
34. Zacks, R. T., & Hasher, L. (2002). Frequency processing: A twenty-five year perspective. In P. Sedlmeier & T. Betsch (Eds.), Frequency Processing and Cognition (pp. 21-36). New York, NY: Oxford University Press. http://dx.doi.org/10.1093/acprof:oso/9780198508632.003.0002