The sunk-cost effect (SCE) is the tendency to continue investing in something that is not working out because of previous investments that cannot be recovered. In three experiments, we examine the SCE when continued investment violates the ethic of care by harming others. In Experiment 1, the SCE was smaller if the sunk-cost decision resulted in harmful consequences towards others (an interaction between sunk cost and the ethic of care). In Experiment 2, participants considered vignettes from their own or another person's perspective. We observed an interpersonal SCE – people showed the SCE when taking the perspective of others. We did not replicate the interaction found in Experiment 1. In Experiment 3, we used statistically more powerful analyses – Bayesian sequential hypothesis testing – to examine the interaction between sunk cost and the ethic of care. We found evidence in favor of the interaction; the SCE was smaller if the sunk-cost decision harmed others. We suggest that violating one’s ethic of care de-biases decision-making by overshadowing sunk costs. These findings may help explain decision-making in real-world situations involving large investments.

We consider a situation in which a group of respondents answers a set of questions and the aim is to identify any consensus among the respondents—that is, shared attitudes, beliefs, or knowledge. Consensus theory postulates that a latent trait determines the respondents’ probability to produce the consensus response. We propose a new version of the variable-response model, which implements consensus theory for numerical continuous responses, ordered categorical responses, unordered categorical responses, or a mixture thereof. The new model also accounts for multiple consensus groups and multiple latent traits underlying the response data. In a series of simulation studies, we identify procedures and conditions that permit an accurate estimation of the number of consensus groups and latent traits. In these simulations, we find that the model recovers the data-generating consensus responses well. We replicate these findings with the empirical data of a memory test.

Interrupting a sequence of episodic recognition decisions by a problem-solving task will change the hit and false alarm rate for the following item in a recognition test (Watkins & Peynircioglu, 1990). The mechanisms of this revelation effect have not yet been understood completely. We offer a new explanation based on the global matching model MINERVA 2 (Hintzman, 1984, 1986, 1988). The main mechanism in our approach is that the interrupting problem-solving task eliminates some context features in the retrieval cue for the next recognition decision. Assuming a constant decision criterion, this shifts the means of the underlying familiarity distributions and produces a revelation effect. The means of the familiarity distributions decrease for low-frequency stimuli but can shift to more positive values for high-frequency stimuli. We show how this approach explains established empirical findings. We also test new predictions within three experiments. The first two experiments show that the revelation effect disappears if context features are made more available at test. The third experiment confirms the prediction that the revelation effect increases as a function of pre-experimental frequency. Overall, our approach explains findings that have been difficult to explain so far, provides a framework for new predictions, and shows connections to other memory paradigms via the underlying model.

The robustness of effects indicating a spatial component associated with abstract reasoning is tested. Judgements regarding hierarchical orderings tend to be faster and more accurate when the dominant element in any pair from the order (e.g., the older, richer) is presented on the left of the screen as compared with the right (left-anchoring effect). This signature effect is investigated in three conditions (Experiment 1), each implementing a different timing regime for the elements in each pair, during learning. Thereby, the construction of a mental representation of the ordering was exposed to a potentially competing spatial simulation, that is, the well-known "mental timeline" with orientation from left (present) to right (future). First, the left-anchoring effect for order representations remained significant when timeline information was congruent with the presumed left-anchoring process, that is, the dominant element in a pair was always presented first. Second, the same effect remained also significant when the timeline-related information was random, that is, the dominant element being presented either first or second. Third, the same effect was found to be still significant, when the timeline-related information was contrary to the left-anchoring process, that is, the dominant element being presented always second. Experiment 2 replicates the target effect under random timeline information, controlling for colour as a stimulus feature. The results are discussed in the context of a theoretical model that integrates basic assumptions about acquired reading/writing habits as a scaffold for spatial simulation and primacy/dominance representation within such spatial simulations.

We consider the proposition that reasoners represent causal conditionals such as "if John studies hard, he will do well in the test" as a causal model in which the antecedent (John studies hard) is a potential cause of the consequent (John does well in the test). Some studies suggest that reasoners ignore alternative causes of the consequent in predictive judgments. Similarly, reasoners may not fully consider alternative causes in diagnostic judgments either. We tested these assumptions in a comparison of 2 causal models with and without alternative causes. In Experiments 1 and 2, only the model with alternative causes tended to overestimate predictive and diagnostic judgments. In Experiment 3, we tested whether the causal models account for the participants' judgments of the probability of the conditional. However, neither model's predictions were accurate. Based on the assumption that probability judgments only follow ordinal relations, we tested qualitative, rather than quantitative predictions of the causal models in Experiments 4 and 5. Participants provided predictive and diagnostic judgments for causal scenarios they observed in the experiments. The results suggest that reasoners consider alternative causes. Finally, in Experiment 6, participants considered pairs of causal conditionals, matched in causal power but differing in the probability of alternative causes. On average, participants preferred to bet on the predictive conclusions of those conditionals that had a higher probability of alternative causes. Because of the uncertain metric properties of probability judgments, we conclude that reasoners likely consider alternative causes in predictive and diagnostic judgments. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

Author Note Correspondence should be addressed to Ulrich von Hecker, School of Psychology, Cardiff University, Tower Building, Park Place, Cardiff, CF10 3AT, United Kingdom. Electronic mail may be sent to vonheckeru@cardiff.ac.uk. We would like to thank Dr. Rainer Leonhart for technical help as well as Sascha Topolinski and an anonymous reviewer for helpful comments on an earlier version. We also thank the Editor Dirk Wentura for helpful suggestions. This research was preregistered with Open Science Framework, see https://osf.io/emauf and https://osf.io/6sznj/.

Measuring shared beliefs, expert consensus, or the details of a crime in eyewitness testimony represents a psychometric challenge. In expert interviews, for example, the correct responses representing the expert consensus (i.e., the answer key) are initially unknown and experts may differ in their contribution to this consensus. I propose the variable-response model, an extension of latent-trait models. The model allows the estimation of the answer key and the latent trait for continuous, categorical, or mixed responses. I describe some minimal requirements for the addition of new response formats to the model. I further propose a Markov chain Monte Carlo algorithm to estimate the model parameters. The results of a simulation study demonstrate that the algorithm accurately recovers the data-generating parameters. I also present an application of the variable-response model to the empirical data of a Geography test. In this application, the parameter estimates correspond well with the true answer key.

Judgments can depend on the activity directly preceding them. An example is the revelation effect whereby participants are more likely to claim that a stimulus is familiar after a preceding task, such as solving an anagram, than without a preceding task. We test conflicting predictions of four revelation-effect hypotheses in a meta-analysis of 26 years of revelation-effect research. The hypotheses’ predictions refer to three subject areas: (1) the basis of judgments that are subject to the revelation effect (recollection vs. familiarity vs. fluency), (2) the degree of similarity between the task and test item, and (3) the difficulty of the preceding task. We use a hierarchical multivariate meta-analysis to account for dependent effect sizes and variance in experimental procedures. We test the revelation-effect hypotheses with a model selection procedure, where each model corresponds to a prediction of a revelation-effect hypothesis. We further quantify the amount of evidence for one model compared to another with Bayes factors. The results of this analysis suggest that none of the extant revelation-effect hypotheses can fully account for the data. The general vagueness of revelation-effect hypotheses and the scarcity of data were the major limiting factors in our analyses, emphasizing the need for formalized theories and further research into the puzzling revelation effect.

Egocentric bias is a core feature of autism. This phenomenon has been studied using the false belief task. However, typically developing children who pass categorical (pass or fail) false belief tasks may still show subtle egocentric bias. We examined 7- to 13-year-old children with autism spectrum disorder (ASD; n=76) or typical development (n=113) using tasks with a continuous response scale: a modified false belief task and a visual hindsight bias task. All children showed robust egocentric bias on both tasks, but no group effects were found. Our large sample size, coupled with our sensitive tasks and resoundingly null group effects, indicate that children with and without ASD possess more similar egocentric tendencies than previously reported.

Tasks that precede a recognition probe induce a more liberal response criterion than do probes without tasks—the “revelation effect.” For example, participants are more likely to claim that a stimulus is familiar directly after solving an anagram, relative to a condition without an anagram. Revelation effect hypotheses disagree whether hard preceding tasks should produce a larger revelation effect than easy preceding tasks. Although some studies have shown that hard tasks increase the revelation effect as compared to easy tasks, these studies suffered from a confound of task difficulty and task presence. Conversely, other studies have shown that the revelation effect is independent of task difficulty. In the present study, we used new task difficulty manipulations to test whether hard tasks produce larger revelation effects than easy tasks. Participants (N = 464) completed hard or easy preceding tasks, including anagrams (Exps. 1 and 2) and the typing of specific arrow key sequences (Exps. 3–6). With sample sizes typical of revelation effect experiments, the effect sizes of task difficulty on the revelation effect varied considerably across experiments. Despite this variability, a consistent data pattern emerged: Hard tasks produced larger revelation effects than easy tasks. Although the present study falsifies certain revelation effect hypotheses, the general vagueness of revelation effect hypotheses remains.

Aggregating information across multiple testimonies may improve crime reconstructions. However, different aggregation methods are available, and research on which method is best suited for aggregating multiple observations is lacking. Furthermore, little is known about how variance in the accuracy of individual testimonies impacts the performance of competing aggregation procedures. We investigated the superiority of aggregation-based crime reconstructions involving multiple individual testimonies and whether this superiority varied as a function of the number of witnesses and the degree of heterogeneity in witnesses’ ability to accurately report their observations. Moreover, we examined whether heterogeneity in competence levels differentially affected the relative accuracy of two aggregation procedures: a simple majority rule, which ignores individual differences, and the more complex general Condorcet model (Romney et al., Am Anthropol 88(2):313–338, 1986; Batchelder and Romney, Psychometrika 53(1):71–92, 1988), which takes into account differences in competence between individuals. 121 participants viewed a simulated crime and subsequently answered 128 true/false questions about the crime. We experimentally generated groups of witnesses with homogeneous or heterogeneous competences. Both the majority rule and the general Condorcet model provided more accurate reconstructions of the observed crime than individual testimonies. The superiority of aggregated crime reconstructions involving multiple individual testimonies increased with an increasing number of witnesses. Crime reconstructions were most accurate when competences were heterogeneous and aggregation was based on the general Condorcet model. We argue that a formal aggregation should be considered more often when eyewitness testimonies have to be assessed and that the general Condorcet model provides a good framework for such aggregations.

Typically, people are more likely to consider a previously seen or heard statement as true compared to a novel statement. This repetition-based “truth effect” is thought to rely on fluency-truth attributions as the underlying cognitive mechanism. In two experiments, we tested the nature of the fluency-attribution mechanism by means of warning instructions, which informed participants about the truth effect and asked them to prevent it. In Experiment 1, we instructed warned participants to consider whether a statement had already been presented in the experiment to avoid the truth effect. However, warnings did not significantly reduce the truth effect. In Experiment 2, we introduced control questions and reminders to ensure that participants understood the warning instruction. This time, warning reduced, but did not eliminate the truth effect. Assuming that the truth effect relies on fluency-truth attributions, this finding suggests that warned participants could control their attributions but did not disregard fluency altogether when making truth judgments. Further, we found no evidence that participants overdiscount the influence of fluency on their truth judgments.

In recognition tests, participants claim that stimuli appear more familiar after an intervening task (e.g., solving an anagram) than without an intervening task-the revelation effect. In Experiment 1, we warned half of the participants about the revelation effect and asked them to prevent any judgment bias. However, compared to a control group without warning instructions, the revelation effect remained unaltered. In Experiment 2, participants who received warning instructions additionally received accuracy feedback for their recognition judgments. We assumed that feedback would aid participants in detecting any judgment bias. Again, warning instructions and feedback failed to reduce the revelation effect. In Experiment 3, participants demonstrated that they understood the warning instructions and generally believed that they were successful in suppressing the revelation effect. Yet, again, a revelation effect occurred. The experiments suggest that the revelation effect is a robust judgment bias that lies outside of the participants' control.

The same event that appeared unpredictable in foresight can be judged as predictable in hindsight. Hindsight bias clouds judgments in all areas of life, including legal decisions, medical diagnoses, consumer satisfaction, sporting events, and election outcomes. We discuss three theoretical constructs related to hindsight bias: memory, reconstruction bias, and motivation. Attempts to recall foresight knowledge fail because newly acquired knowledge affects memory either directly or indirectly by biasing attempts to reconstruct foresight knowledge. On a metacognitive level, overconfidence and surprise contribute to hindsight bias. Overconfidence in knowledge increases hindsight bias whereas a well-calibrated confidence reduces hindsight bias. Motivational factors also contribute to hindsight bias by making positive and negative outcomes appear more or less likely, depending on a variety of factors. We review hindsight bias theories and discuss three exciting directions for future research.