A Meta-Analytic Re-Appraisal of the Framing Effect

2018 ◽  
Vol 226 (1) ◽  
pp. 45-55 ◽  
Author(s):  
Alexander Steiger ◽  
Anton Kühberger

Abstract. We reevaluated and reanalyzed the data of Kühberger’s (1998) meta-analysis on framing effects in risky decision making by using p-curve. This method uses the distribution of only significant p-values to correct the effect size, thus taking publication bias into account. We found a corrected overall effect size of d = 0.52, which is considerably higher than the effect reported by Kühberger (d = 0.31). Similarly to the original analysis, most moderators proved to be effective, indicating that there is not the risky-choice framing effect. Rather, the effect size varies with different manipulations of the framing task. Taken together, the p-curve analysis shows that there are reliable risky-choice framing effects, and that there is no evidence of intense p-hacking. Comparing the corrected estimate to the effect size reported in the Many Labs Replication Project (MLRP) on gain-loss framing (d = 0.60) shows that the two estimates are surprisingly similar in size. Finally, we conducted a new meta-analysis of risk framing experiments published in 2016 and again found a similar effect size (d = 0.56). Thus, although there is discussion on the adequate explanation for framing effects, there is no doubt about their existence: risky-choice framing effects are highly reliable and robust. No replicability crisis there.

Author(s):  
Raúl A. Borracci ◽  
Eduardo B. Arribalzaga ◽  
Jorge Thierer

Purpose:The framing effect refers to a phenomenon whereby, when the same problem is presented using different representations of information, people make significant changes in their decisions.Itaimed to explore whether theframingeffect could be reduced in medical students and residents by teaching them the statistical concepts of effect size, probability, and sampling to be used in the medical decision-making process.MethodsNinety-five second-year medical students and 100 second-year medical residentsof Austral University and Buenos Aires University, Argentina were invited to participate in the study between March and June 2017. A questionnaire was developed to assess the different types of framing effects in medical situations. After an initial administration of the survey, students and residents were taught statistical concepts including effect size, probability, and sampling during two individual independent official biostatistics courses. After these interventions, the same questionnaire was randomly applied again, and pre- and post-intervention outcomes were compared for students and residents. Results: Almost every type of framing effect was reproduced either in the students or in the resident population. After teaching medical students and residents the analytical process behind statistical notions, a significant reduction in sample-size, risky-choice, pseudo-certainty, number-size, attribute, goal, and probabilistic formulation framing effects was observed. Conclusions Decision-making of medical students and residents in simulated medical situations may be affected by different frame descriptions, and these framing effects can be partially reduced by training individuals in probability analysis and statistical sampling methods.


2020 ◽  
Author(s):  
Samuel Shye ◽  
Ido Haber

Challenge Theory (Shye & Haber 2015; 2020) has demonstrated that a newly devised challenge index (CI) attributable to every binary choice problem predicts the popularity of the bold option, the one of lower probability to gain a higher monetary outcome (in a gain problem); and the one of higher probability to lose a lower monetary outcome (in a loss problem). In this paper we show how Facet Theory structures the choice-behavior concept-space and yields rationalized measurements of gambling behavior. The data of this study consist of responses obtained from 126 student, specifying their preferences in 44 risky decision problems. A Faceted Smallest Space Analysis (SSA) of the 44 problems confirmed the hypothesis that the space of binary risky choice problems is partitionable by two binary axial facets: (a) Type of Problem (gain vs. loss); and (b) CI (Low vs. High). Four composite variables, representing the validated constructs: Gain, Loss, High-CI and Low-CI, were processed using Multiple Scaling by Partial Order Scalogram Analysis with base Coordinates (POSAC), leading to a meaningful and intuitively appealing interpretation of two necessary and sufficient gambling-behavior measurement scales.


2019 ◽  
Author(s):  
Jonathan Charles Corbin

In typical experiments examining the role of gain-loss framing on risky-choice, great care is taken to ensure that the scenarios are generic enough to avoid outside sources of bias. However, policy proposals in the real world that can have significant effects on human lives or involve large sums of money often originate from a partisan source. I examine the extent to which partisan identity influences choice in a standard risky-choice framing paradigm. I also test dual-process theory predictions for how the conflict between partisan loyalty and frame should reduce framing bias (but not partisan bias). Participants were given 12 hypothetical framing problems(6 gain/6 loss) in which the U.S. Congress was entertaining two policy proposals (sure/risky) in each scenario. In 8 of the problems, I manipulated which political party (Republican/Democrat) proposed which option. In the remaining 4, both options are bipartisan (Plan A/Plan B). I also measured participants’ partisan identity. Consistent with standard framing, participants were more risk-averse when options were framed as gains and more risk seeking when framed as losses. However, independent of the effect of frame, decision-makers’ risk-preferences also shifted in favor of their preferred party’s proposal. Data, syntax, and preregistration can be found at https://osf.io/gcbez/.


2020 ◽  
Vol 7 (4) ◽  
pp. 1
Author(s):  
Samuel Shye ◽  
Ido Haber

Challenge Theory (Shye & Haber 2015; 2020) has demonstrated that a newly devised challenge index (CI) attributable to every binary choice problem predicts the popularity of the bold option, the one of lower probability to gain a higher monetary outcome (in a gain problem); and the one of higher probability to lose a lower monetary outcome (in a loss problem).  In this paper we show how Facet Theory structures the choice-behavior concept-space and yields rationalized measurements of gambling behavior. The data of this study consist of responses obtained from 126 student, specifying their preferences in 44 risky decision problems. A Faceted Smallest Space Analysis (SSA) of the 44 problems confirmed the hypothesis that the space of binary risky choice problems is partitionable by two binary axial facets: (a) Type of Problem (gain vs. loss); and (b) CI (Low vs. High). Four composite variables, representing the validated constructs: Gain, Loss, High-CI and Low-CI, were processed using Multiple Scaling by Partial Order Scalogram Analysis with base Coordinates (POSAC), leading to a meaningful and intuitively appealing interpretation of two necessary and sufficient gambling-behavior measurement scales.


2021 ◽  
Author(s):  
Sarah A. Fisher ◽  
David R. Mandel

This article surveys the latest research on risky-choice framing effects, focusing on the implications for rational decision-making. An influential program of psychological research suggests that people’s judgements and decisions depend on the way in which information is presented, or ‘framed’. In a central choice paradigm, decision-makers seem to adopt different preferences, and different attitudes to risk, depending on whether the options specify the number of people who will be saved or the corresponding number who will die. It is standardly assumed that such responses violate a foundational tenet of rational decision-making, known as the principle of description invariance. We discuss recent theoretical and empirical research that challenges the dominant ‘irrationalist’ narrative. These approaches typically pay close attention to how decision-makers represent decision problems (including their interpretation of numerical quantifiers or predicate choice) and they highlight the need for a more robust characterization of the description invariance principle. We conclude by indicating avenues for future research that could bring us closer to a complete – and potentially rationalizing – explanation of framing effects.


PLoS ONE ◽  
2021 ◽  
Vol 16 (9) ◽  
pp. e0257151
Author(s):  
Nikolay R. Rachev ◽  
Hyemin Han ◽  
David Lacko ◽  
Rebekah Gelpí ◽  
Yuki Yamada ◽  
...  

In the risky-choice framing effect, different wording of the same options leads to predictably different choices. In a large-scale survey conducted from March to May 2020 and including 88,181 participants from 47 countries, we investigated how stress, concerns, and trust moderated the effect in the Disease problem, a prominent framing problem highly evocative of the COVID-19 pandemic. As predicted by the appraisal-tendency framework, risk aversion and the framing effect in our study were larger than under typical circumstances. Furthermore, perceived stress and concerns over coronavirus were positively associated with the framing effect. Contrary to predictions, however, they were not related to risk aversion. Trust in the government’s efforts to handle the coronavirus was associated with neither risk aversion nor the framing effect. The proportion of risky choices and the framing effect varied substantially across nations. Additional exploratory analyses showed that the framing effect was unrelated to reported compliance with safety measures, suggesting, along with similar findings during the pandemic and beyond, that the effectiveness of framing manipulations in public messages might be limited. Theoretical and practical implications of these findings are discussed, along with directions for further investigations.


2013 ◽  
Vol 5 (9) ◽  
pp. 2846-2850
Author(s):  
Qishen Zhou ◽  
Hua Liu ◽  
Jiang Liu ◽  
Rui Kang ◽  
Yiling Huang

2018 ◽  
Vol 49 (5) ◽  
pp. 303-309 ◽  
Author(s):  
Jedidiah Siev ◽  
Shelby E. Zuckerman ◽  
Joseph J. Siev

Abstract. In a widely publicized set of studies, participants who were primed to consider unethical events preferred cleansing products more than did those primed with ethical events ( Zhong & Liljenquist, 2006 ). This tendency to respond to moral threat with physical cleansing is known as the Macbeth Effect. Several subsequent efforts, however, did not replicate this relationship. The present manuscript reports the results of a meta-analysis of 15 studies testing this relationship. The weighted mean effect size was small across all studies (g = 0.17, 95% CI [0.04, 0.31]), and nonsignificant across studies conducted in independent laboratories (g = 0.07, 95% CI [−0.04, 0.19]). We conclude that there is little evidence for an overall Macbeth Effect; however, there may be a Macbeth Effect under certain conditions.


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