Literature DB >> 28504522

The construct-behavior gap in behavioral decision research: A challenge beyond replicability.

Michel Regenwetter1, Maria M Robinson1.   

Abstract

Behavioral decision research compares theoretical constructs like preferences to behavior such as observed choices. Three fairly common links from constructs to behavior are (1) to tally, across participants and decision problems, the number of choices consistent with one predicted pattern of pairwise preferences; (2) to compare what most people choose in each decision problem against a predicted preference pattern; or (3) to enumerate the decision problems in which two experimental conditions generate a 1-sided significant difference in choice frequency 'consistent' with the theory. Although simple, these theoretical links are heuristics. They are subject to well-known reasoning fallacies, most notably the fallacy of sweeping generalization and the fallacy of composition. No amount of replication can alleviate these fallacies. On the contrary, reiterating logically inconsistent theoretical reasoning over and again across studies obfuscates science. As a case in point, we consider pairwise choices among simple lotteries and the hypotheses of overweighting or underweighting of small probabilities, as well as the description-experience gap. We discuss ways to avoid reasoning fallacies in bridging the conceptual gap between hypothetical constructs, such as, for example, "overweighting" to observable pairwise choice data. Although replication is invaluable, successful replication of hard-to-interpret results is not. Behavioral decision research stands to gain much theoretical and empirical clarity by spelling out precise and formally explicit theories of how hypothetical constructs translate into observable behavior. (PsycINFO Database Record (c) 2017 APA, all rights reserved).

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Year:  2017        PMID: 28504522     DOI: 10.1037/rev0000067

Source DB:  PubMed          Journal:  Psychol Rev        ISSN: 0033-295X            Impact factor:   8.934


  11 in total

1.  Predictive cues reduce but do not eliminate intrinsic response bias.

Authors:  Mingjia Hu; Dobromir Rahnev
Journal:  Cognition       Date:  2019-06-21

2.  Mechanisms of output interference in cued recall.

Authors:  Jack H Wilson; David Kellen; Amy H Criss
Journal:  Mem Cognit       Date:  2020-01

Review 3.  Three gaps and what they may mean for risk preference.

Authors:  Ralph Hertwig; Dirk U Wulff; Rui Mata
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2019-02-18       Impact factor: 6.237

4.  Testing Probabilistic Models of Choice using Column Generation.

Authors:  Bart Smeulders; Clintin Davis-Stober; Michel Regenwetter; Frits C R Spieksma
Journal:  Comput Oper Res       Date:  2018-03-08       Impact factor: 4.008

5.  The 'paradox' of converging evidence.

Authors:  Clintin P Davis-Stober; Michel Regenwetter
Journal:  Psychol Rev       Date:  2019-08-15       Impact factor: 8.934

6.  Toward a more comprehensive modeling of sequential lineups.

Authors:  David Kellen; Ryan M McAdoo
Journal:  Cogn Res Princ Implic       Date:  2022-07-22

Review 7.  Measuring memory is harder than you think: How to avoid problematic measurement practices in memory research.

Authors:  Timothy F Brady; Maria M Robinson; Jamal R Williams; John T Wixted
Journal:  Psychon Bull Rev       Date:  2022-10-19

8.  Cognitive Aging and Tests of Rationality.

Authors:  Sanghyuk Park; Clintin P Davis-Stober; Hope K Snyder; William Messner; Michel Regenwetter
Journal:  Span J Psychol       Date:  2019-12-23       Impact factor: 1.264

9.  How conformity can lead to polarised social behaviour.

Authors:  Folco Panizza; Alexander Vostroknutov; Giorgio Coricelli
Journal:  PLoS Comput Biol       Date:  2021-10-20       Impact factor: 4.475

10.  Experience and rationality under risk: re-examining the impact of sampling experience.

Authors:  Ilke Aydogan; Yu Gao
Journal:  Exp Econ       Date:  2020-01-16
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