bluuebunny/crossref_metadata_2025_split huggingface dataset:
Using hierarchical Bayesian methods to examine the tools of decision-making
Authors: Lee Michael D. , Newell Benjamin R. 
Published: January 2023

AbstractHierarchical Bayesian methods offer a principled and comprehensive way to relate psychological models to data. Here we use them to model the patterns of information search, stopping and deciding in a simulated binary comparison judgment task. The simulation involves 20 subjects making 100 forced choice comparisons about the relative magnitudes of two objects (which of two German cities has more inhabitants). Two worked-examples show how hierarchical models can be developed to account for and explain the diversity of both search and stopping rules seen across the simulated individuals. We discuss how the results provide insight into current debates in the literature on heuristic decision making and argue that they demonstrate the power and flexibility of hierarchical Bayesian methods in modeling human decision-making.
A model-based approach for the analysis of the calibration of probability judgments
Authors: Budescu David V. , Johnson Timothy R. 
Published: January 2023

AbstractThe calibration of probability or confidence judgments concerns the association between the judgments and some estimate of the correct probabilities of events. Researchers rely on estimates using relative frequencies computed by aggregating data over observations. We show that this approach creates conceptual problems, and may result in the confounding of explanatory variables or unstable estimates. To circumvent these problems we propose using probability estimates obtained from statistical models—specifically mixed models for binary data—in the analysis of calibration. We illustrate this methodology by re-analyzing data from a published study and comparing the results from this approach to those based on relative frequencies. The model-based estimates avoid problems with confounding variables and provided more precise estimates, resulting in better inferences.
Is there evidence of publication biases in JDM research?
Authors: Renkewitz Frank , Fuchs Heather M. , Fiedler Susann 
Published: January 2023

AbstractIt is a long known problem that the preferential publication of statistically significant results (publication bias) may lead to incorrect estimates of the true effects being investigated. Even though other research areas (e.g., medicine, biology) are aware of the problem, and have identified strong publication biases, researchers in judgment and decision making (JDM) largely ignore it. We reanalyzed two current meta-analyses in this area. Both showed evidence of publication biases that may have led to a substantial overestimation of the true effects they investigated. A review of additional JDM meta-analyses shows that most meta-analyses conducted no or insufficient analyses of publication bias. However, given our results and the rareness of non-significant effects in the literature, we suspect that biases occur quite often. These findings suggest that (a) conclusions based on meta-analyses without reported tests of publication bias should be interpreted with caution and (b) publication policies and standard research practices should be revised to overcome the problem.
Too soon to tell if the US intelligence community prediction market is more accurate than intelligence reports: Commentary on
Authors: Mandel David R. 
Published: January 2023

AbstractStastny and Lehner (2018) reported a study comparing the forecast accuracy of a US intelligence community prediction market (ICPM) to traditionally produced intelligence reports. Five analysts unaffiliated with the intelligence reports imputed forecasts from the reports after stating their personal forecasts on the same forecasting questions. The authors claimed that the accuracy of the ICPM was significantly greater than that of the intelligence reports and suggest this may have been due to methods that harness crowd wisdom. However, additional analyses conducted here show that the imputer’s personal forecasts, which were made individually, were as accurate as ICPM forecasts. In fact, their updated personal forecasts (made after reading the intelligence reports) were marginally more accurate than ICPM forecasts. Imputed forecasts are also strongly correlated with the imputers’ personal forecasts, casting doubt on the degree to which the imputation was in fact a reliably inter-subjective assessment of what intelligence reports implied about the forecasting questions. Alternative methods for comparing intelligence community forecasting methods are discussed.
Why dyads heed advice less than individuals do
Authors: Schultze Thomas , Mojzisch Andreas , Schulz-Hardt Stefan 
Published: January 2023

AbstractFollowing up on a recent debate, we examined advice taking in dyads compared to individuals in a set of three studies (total N = 303 dyads and 194 individuals). Our first aim was to test the replicability of an important previous finding, namely that dyads heed advice less than individuals because they feel more confident in the accuracy of their initial judgments. Second, we aimed to explain dyads’ behavior based on three premises: first, that dyads understand that the added value of an outside opinion diminishes when the initial pre-advice judgment is made by two judges rather than one judge (given that the dyad members’ opinions are independent of each other); second, that they fail to recognize when the assumption of independence of opinions does not hold; and third, that the resistance to advice commonly observed in individuals persists in groups but is neither aggravated nor ameliorated by the group context. The results of our studies show consistently that previous findings on advice taking in dyads are replicable. They also support our hypothesis that groups exhibit a general tendency to heed advice less than individuals, irrespective of whether the accuracy of their initial judgments warrants this behavior. Finally, based on the three assumptions mentioned above, we were able to make accurate predictions about advice taking in dyads, prompting us to postulate a general model of advice taking in groups of arbitrary size.
Savings, subgoals, and reference points
Authors: Colby Helen , Chapman Gretchen B. 
Published: January 2023

AbstractDecision makers often save money for a specific goal by forgoing discretionary consumption and instead putting the money toward the savings goal. We hypothesized that reference points can be exploited to enhance this type of saving. In two hypothetical scenario studies, subjects made judgments of their likelihood to forgo a small expenditure in order to put the money toward the savings goal. In Experiment 1, judgments were higher if the savings goal was presented as composed of weekly subgoals (e.g., save $60 per week to buy a $180 iPod). Experiment 2 replicated this finding and demonstrated that the subgoal manipulation increased judgments of likelihood to save money only when the money saved from the foregone consumption would allow the decision maker to meet the weekly subgoal exactly (not under or overshoot it). These results suggest a reference point mechanism and point to ways that behavioral decision research can be harnessed to improve economic behaviors.
Reply: Birnbaum’s (2012) statistical tests of independence have unknown Type-I error rates and do not replicate within participant
Authors: Cha Yun-shil , Choi Michelle , Guo Ying , Regenwetter Michel , Zwilling Chris 
Published: January 2023

AbstractBirnbaum (2011, 2012) questioned the iid (independent and identically distributed) sampling assumptions used by state-of-the-art statistical tests in Regenwetter, Dana and Davis-Stober’s (2010, 2011) analysis of the “linear order model”. Birnbaum (2012) cited, but did not use, a test of iid by Smith and Batchelder (2008) with analytically known properties. Instead, he created two new test statistics with unknown sampling distributions.Our rebuttal has five components: 1) We demonstrate that the Regenwetter et al. data pass Smith and Batchelder’s test of iid with flying colors. 2) We provide evidence from Monte Carlo simulations that Birnbaum’s (2012) proposed tests have unknown Type-I error rates, which depend on the actual choice probabilities and on how data are coded as well as on the null hypothesis of iid sampling. 3) Birnbaum analyzed only a third of Regenwetter et al.’s data. We show that his two new tests fail to replicate on the other two-thirds of the data, within participants. 4) Birnbaum selectively picked data of one respondent to suggest that choice probabilities may have changed partway into the experiment. Such nonstationarity could potentially cause a seemingly good fit to be a Type-II error. We show that the linear order model fits equally well if we allow for warm-up effects. 5) Using hypothetical data, Birnbaum (2012) claimed to show that “true-and-error” models for binary pattern probabilities overcome the alleged short-comings of Regenwetter et al.’s approach. We disprove this claim on the same data.
Proportion dominance in valuing lives: The role of deliberative thinking
Authors: Mata André 
Published: January 2023

AbstractProportion responding (PR) is the preference for proportionally higher gains, such that the same absolute quantity is valued more as the reference group decreases. This research investigated this kind of proportion PR in decisions about saving lives (e.g., saving 10/10 lives is preferred to saving 10/100 lives). The results of two studies suggest that PR does not stem from an overall tendency to choose higher proportions, but rather from faulty deliberative reasoning. In particular, people who display PR are less likely to engage in deliberative reflection as measured by response time, the Process Dissociation Procedure, the Cognitive Reflection Test, a numeracy test, and a task assessing denominator neglect. This association between faulty deliberation and PR was observed only when choosing the highest proportion was non-normative because it came at the expense of absolute gains (e.g., saving 10/10 lives is preferred to saving 11/100 lives). These results help to make sense of discrepant findings in previous research, pertaining to how PR relates to biased reasoning and decision making.
The effectiveness of imperfect weighting in advice taking
Authors: Bednarik Peter , Schultze Thomas 
Published: January 2023

AbstractWe investigate decision-making in the Judge-Advisor-System where one person, the “judge”, wants to estimate the number of a certain entity and is given advice by another person. The question is how to combine the judge’s initial estimate and that of the advisor in order to get the optimal expected outcome. A previous approach compared two frequently applied strategies, taking the average or choosing the better estimate. In most situations, averaging produced the better estimates. However, this approach neglected a third strategy that judges frequently use, namely a weighted mean of the judges’ initial estimate and the advice. We compare the performance of averaging and choosing to weighting in a theoretical analysis. If the judge can, without error, detect ability differences between judge and advisor, a straight-forward calculation shows that weighting outperforms both of these strategies. More interestingly, after introducing errors in the perception of the ability differences, we show that such imperfect weighting may or may not be the optimal strategy. The relative performance of imperfect weighting compared to averaging or choosing depends on the size of the actual ability differences as well as the magnitude of the error. However, for a sizeable range of ability differences and errors, weighting is preferable to averaging and more so to choosing. Our analysis expands previous research by showing that weighting, even when imperfect, is an appropriate advice taking strategy and under which circumstances judges benefit most from applying it.
Predicting biases in very highly educated samples: Numeracy and metacognition
Authors: Ghazal Saima , Cokely Edward T. , Garcia-Retamero Rocio 
Published: January 2023

AbstractWe investigated the relations between numeracy and superior judgment and decision making in two large community outreach studies in Holland (n=5408). In these very highly educated samples (e.g., 30–50% held graduate degrees), the Berlin Numeracy Test was a robust predictor of financial, medical, and metacognitive task performance (i.e., lotteries, intertemporal choice, denominator neglect, and confidence judgments), independent of education, gender, age, and another numeracy assessment. Metacognitive processes partially mediated the link between numeracy and superior performance. More numerate participants performed better because they deliberated more during decision making and more accurately evaluated their judgments (e.g., less overconfidence). Results suggest that well-designed numeracy tests tend to be robust predictors of superior judgment and decision making because they simultaneously assess (1) mathematical competency and (2) metacognitive and self-regulated learning skills.
On the role of recognition in consumer choice: A model comparison
Authors: Hilbig Benjamin E. 
Published: January 2023

AbstractOne prominent model in the realm of memory-based judgments and decisions is the recognition heuristic. Under certain preconditions, it presumes that choices are based on recognition in a one-cue non-compensatory manner and that other information is ignored. This claim has been studied widely—and received, at best, mixed support—in probabilistic inferences. By contrast, only a small number of recent investigations have taken the RH to the realm of preferential decisions (i.e. consumer choice). So far, the conclusion has been that the RH cannot satisfactorily account for aggregate data patterns, but no fully specified alternative model has been demonstrated to provide a better account. Herein, the data from a recent consumer-choice study (Thoma & Williams, 2013) are re-analyzed with the outcome-based maximum-likelihood strategy classification method, thus testing several competing models on individual data. Results revealed that an alternative compensatory model (an equal weights strategy) accounted best for a larger number of datasets than the RH. Thereby, the findings further specify prior results and answer the call for comparative model testing on individual data that has been voiced repeatedly.
Survey of time preference, delay discounting models
Authors: Doyle John R. 
Published: January 2023

AbstractThe paper surveys over twenty models ofdelay discounting(also known astemporal discounting, time preference, time discounting), that psychologists and economists have put forward to explain the way people actually trade off time and money. Using little more than the basic algebra of powers and logarithms, I show how the models are derived, what assumptions they are based upon, and how different models relate to each other. Rather than concentrate only ondiscount functionsthemselves, I show how discount functions may be manipulated to isolaterate parametersfor each model. This approach, consistently applied, helps focus attention on the three main components in any discounting model: subjectively perceived money; subjectively perceived time; and how these elements are combined. We group models by the number of parameters that have to be estimated, which means our exposition follows a trajectory of increasing complexity to the models. However, as the story unfolds it becomes clear that most models fall into a smaller number of families. We also show how new models may be constructed by combining elements of different models.The surveyed models are: Exponential; Hyperbolic; Arithmetic; Hyperboloid (Green & Myerson, Rachlin); Loewenstein and Prelec Generalized Hyperboloid; quasi-Hyperbolic (also known asβ-δdiscounting); Benhabib et al’s fixed cost; Benhabib et al’s Exponential / Hyperbolic / quasi-Hyperbolic; Read’s discounting fractions; Roelofsma’s exponential time; Scholten and Read’s discounting-by-intervals (DBI); Ebert and Prelec’s constant sensitivity (CS); Bleichrodt et al.’s constant absolute decreasing impatience (CADI); Bleichrodt et al.’s constant relative decreasing impatience (CRDI); Green, Myerson, and Macaux’s hyperboloid over intervals models; Killeen’s additive utility; size-sensitive additive utility; Yi, Landes, and Bickel’s memory trace models; McClure et al.’s two exponentials; and Scholten and Read’s trade-off model.For a convenient overview, a single “cheat sheet” table captures the notation and essential mathematics behind all but one of the models.
Regret salience and accountability in the decoy effect
Authors: Connolly Terry , Reb Jochen , Kausel Edgar E. 
Published: January 2023

AbstractTwo experiments examined the impact on the decoy effect of making salient the possibility of post-decision regret, a manipulation that has been shown in several earlier studies to stimulate critical examination and improvement of decision process. Experiment 1 (N = 62) showed that making regret salient eliminated the decoy effect in a personal preference task. Experiment 2 (N = 242) replicated this finding for a different personal preference task and for a prediction task. It also replicated previous findings that external accountability demands do not reduce, and may exacerbate, the decoy effect. We interpret both effects in terms of decision justification, with different justification standards operating for different audiences. The decoy effect, in this account, turns on accepting a weak justification, which may be seen as adequate for an external audience or one’s own inattentive self but inadequate under the more critical review triggered by making regret possibilities salient. Seeking justification to others (responding to accountability demands) thus maintains or exacerbates the decoy effect; seeking justification to oneself (responding to regret salience) reduces or eliminates it. The proposed mechanism provides a theoretical account both of the decoy effect itself and of how regret priming provides an effective debiasing procedure for it.
Risky choice in younger versus older adults: Affective context matters
Authors: Huang Yumi , Wood Stacey , Berger Dale , Hanoch Yaniv 
Published: January 2023

AbstractEarlier frameworks have indicated that older adults tend to experience decline in their deliberative decisional capacity, while their affective abilities tend to remain intact (Peters, Hess, Västfjäll, & Auman, 2007). The present study applied this framework to the study of risky decision-making across the lifespan. Two versions of the Columbia Card Task (CCT) were used to trigger either affective decision-making (i.e., the “warm” CCT) or deliberative decision-making (i.e., the “cold” CCT) in a sample of 158 individuals across the lifespan. Overall there were no age differences in risk seeking. However, there was a significant interaction between age and condition, such that older adults were relatively more risk seeking in the cold condition only. In terms of everyday decision-making, context matters and risk propensity may shift within older adults depending upon the context.
How the number of options and perceived variety influence choice satisfaction: An experiment with prescription drug plans
Authors: Szrek Helena 
Published: January 2023

AbstractThis study measures the perceived costs, perceived benefits, choice outcome satisfaction, and choice process satisfaction from consumers making hypothetical choices amongst prescription drug plans. I juxtapose the number of options the consumer is choosing between and his/her perceived variety of the choice set to understand which contributes more to explaining these outcomes. I find that once perceived variety is included in the model, the number of options (i) has no effect on perceived benefits and choice outcome satisfaction, (ii) increases perceived costs, and (iii) decreases choice process satisfaction. Furthermore, the concave relationship that has been shown to occur when the number of options increases is a function of the subjective perception of variety. Overall, these results contribute to our understanding of how assortment structure and the number of options affect choice outcome and process satisfaction. Additionally, this study provides some evidence that can inform U.S. national heath insurance policy and the current debate on choice in health care in the United States and other countries.
DOSPERT+M: A survey of medical risk attitudes in the United States
Authors: Rosman Adam , Garcia Maggie , Lee Sam , Butler Shoshana , Schwartz Alan 
Published: January 2023

AbstractBackground:The Domain-Specific Risk Taking scale (DOSPERT) has been recommended as a tool for measuring risk attitudes in medical studies, but does not contain items specific to health care. Butler, et al. (2012) developed a medical risk domain subscale for DOSPERT.Objective:To characterize medical risk attitudes in a nationally-representative U.S. sample using the full DOSPERT scale with the medical risk domain add-on (DOSPERT+M), and examine associations with other risk domains.Methods:Members of a nationally-representative online panel (KnowledgePanel®) were randomized to complete pairs of DOSPERT+M tasks (risk attitude, risk perception, expected benefits). We explored relationships among domains through correlational and factor analysis; we tested the hypothesis that the medical risk domain and DOSPERT’s health/safety domains were not highly correlated.Participants:Three hundred forty-four panelists.Results:The medical risk domain subscale had low inter-item reliability in the risk-taking task and moderate inter-item reliability in the other tasks. Medical risk domain scores were poorly correlated with the DOSPERT health/safety domain. Exploratory factor analysis largely recovered the expected DOSPERT domain structure.Conclusion:Attitudes toward risky medical activities may constitute a distinct domain from those measured by the standard DOSPERT items. Additional work is required to develop a medical risk subscale with higher inter-item reliability.
How the public, and scientists, perceive advancement of knowledge from conflicting study results
Authors: Koehler Derek J. , Pennycook Gordon 
Published: January 2023

AbstractScience often advances through disagreement among scientists and the studies they produce. For members of the public, however, conflicting results from scientific studies may trigger a sense of uncertainty that in turn leads to a feeling that nothing new has been learned from those studies. In several scenario studies, participants read about pairs of highly similar scientific studies with results that either agreed or disagreed, and were asked, “When we take the results of these two studies together, do we now know more, less, or the same as we did before about (the study topic)?” We find that over half of participants do not feel that “we know more” as the result of the two new studies when the second study fails to replicate the first. When the two study results strongly conflict (e.g., one finds a positive and the other a negative association between two variables), a non-trivial proportion of participants actually say that “we know less” than we did before. Such a sentiment arguably violates normative principles of statistical and scientific inference positing that new study findings can never reduce our level of knowledge (and that only completely uninformative studies can leave our level of knowledge unchanged). Drawing attention to possible moderating variables, or to sample size considerations, did not influence people’s perceptions of knowledge advancement. Scientist members of the American Academy of Arts and Sciences, when presented with the same scenarios, were less inclined to say that nothing new is learned from conflicting study results.