ORCID Profile
0000-0002-9019-6574
Current Organisation
Indiana University
Does something not look right? The information on this page has been harvested from data sources that may not be up to date. We continue to work with information providers to improve coverage and quality. To report an issue, use the Feedback Form.
Publisher: Springer Science and Business Media LLC
Date: 15-02-2018
Publisher: Proceedings of the National Academy of Sciences
Date: 12-03-2018
Abstract: We describe and demonstrate an empirical strategy useful for discovering and replicating empirical effects in psychological science. The method involves the design of a metastudy, in which many independent experimental variables—that may be moderators of an empirical effect—are indiscriminately randomized. Radical randomization yields rich datasets that can be used to test the robustness of an empirical claim to some of the vagaries and idiosyncrasies of experimental protocols and enhances the generalizability of these claims. The strategy is made feasible by advances in hierarchical Bayesian modeling that allow for the pooling of information across unlike experiments and designs and is proposed here as a gold standard for replication research and exploratory research. The practical feasibility of the strategy is demonstrated with a replication of a study on subliminal priming.
Publisher: Informa UK Limited
Date: 26-06-2015
Publisher: American Psychological Association (APA)
Date: 10-2015
DOI: 10.1037/A0039656
Abstract: Trueblood, Brown, and Heathcote (2014) developed a new model, called the multiattribute linear ballistic accumulator (MLBA), to explain contextual preference reversals in multialternative choice. MLBA was shown to provide good accounts of human behavior through both qualitative analyses and quantitative fitting of choice data. Tsetsos, Chater, and Usher (2015) investigated the ability of MLBA to simultaneously capture 3 prominent context effects (attraction, compromise, and similarity). They concluded that MLBA must set a "fine balance" of competing forces to account for all 3 effects simultaneously and that its predictions are sensitive to the position of the stimuli in the attribute space. Through a new experiment, we show that the 3 effects are very fragile and that only a small subset of people shows all 3 simultaneously. Thus, the predictions that Tsetsos et al. generated from the MLBA model turn out to match closely real data in a new experiment. Support for these predictions provides strong evidence for the MLBA. A corollary is that a model that can "robustly" capture all 3 effects simultaneously is not necessarily a good model. Rather, a good model captures patterns found in human data, but cannot accommodate patterns that are not found.
Publisher: American Psychological Association (APA)
Date: 2021
DOI: 10.1037/REV0000255
Publisher: American Psychological Association (APA)
Date: 04-2014
DOI: 10.1037/A0036137
Abstract: Context effects occur when a choice between 2 options is altered by adding a 3rd alternative. Three major context effects--similarity, compromise, and attraction--have wide-ranging implications across applied and theoretical domains, and have driven the development of new dynamic models of multiattribute and multialternative choice. We propose the multiattribute linear ballistic accumulator (MLBA), a new dynamic model that provides a quantitative account of all 3 context effects. Our account applies not only to traditional paradigms involving choices among hedonic stimuli, but also to recent demonstrations of context effects with nonhedonic stimuli. Because of its computational tractability, the MLBA model is more easily applied than previous dynamic models. We show that the model also accounts for a range of other phenomena in multiattribute, multialternative choice, including time pressure effects, and that it makes a new prediction about the relationship between deliberation time and the magnitude of the similarity effect, which we confirm experimentally.
Publisher: Wiley
Date: 03-03-2014
DOI: 10.1111/ADD.12494
Abstract: To analyse problem gamblers' decision-making under conditions of risk and ambiguity, investigate underlying psychological factors associated with their choice behaviour and examine whether decision-making differed in strategic (e.g., sports betting) and non-strategic (e.g., electronic gaming machine) problem gamblers. Cross-sectional study. Out-patient treatment centres and university testing facilities in Victoria, Australia. Thirty-nine problem gamblers and 41 age, gender and estimated IQ-matched controls. Decision-making tasks included the Iowa Gambling Task (IGT) and a loss aversion task. The Prospect Valence Learning (PVL) model was used to provide an explanation of cognitive, motivational and response style factors involved in IGT performance. Overall, problem gamblers performed more poorly than controls on both the IGT (P = 0.04) and the loss aversion task (P = 0.01), and their IGT decisions were associated with heightened attention to gains (P = 0.003) and less consistency (P = 0.002). Strategic problem gamblers did not differ from matched controls on either decision-making task, but non-strategic problem gamblers performed worse on both the IGT (P = 0.006) and the loss aversion task (P = 0.02). Furthermore, we found differences in the PVL model parameters underlying strategic and non-strategic problem gamblers' choices on the IGT. Problem gamblers demonstrated poor decision-making under conditions of risk and ambiguity. Strategic (e.g. sports betting, poker) and non-strategic (e.g. electronic gaming machines) problem gamblers differed in decision-making and the underlying psychological processes associated with their decisions.
Publisher: Center for Open Science
Date: 31-08-2019
Abstract: The target article on robust modeling (Lee et al.) generated a lot of commentary. In this reply, we discuss some of the common themes in the commentaries some are simple points of agreement while others are extensions of a practical or abstract nature. We also address a small number of disagreements or confusions.
Publisher: Elsevier BV
Date: 03-2016
Publisher: SAGE Publications
Date: 22-04-2013
Abstract: Context effects—preference changes that depend on the availability of other options—have attracted a great deal of attention among consumer researchers studying high-level decision tasks. In the experiments reported here, we showed that these effects also arise in simple perceptual-decision-making tasks. This finding casts doubt on explanations limited to consumer choice and high-level decisions, and it indicates that context effects may be amenable to a general explanation at the level of the basic decision process. We demonstrated for the first time that three important context effects from the preferential-choice literature—similarity, attraction, and compromise effects—all occurred within a single perceptual-decision task. Not only do our results challenge previous explanations for context effects proposed by consumer researchers, but they also challenge the choice rules assumed in theories of perceptual decision making.
Publisher: Oxford University Press (OUP)
Date: 31-12-2021
Abstract: Medical image interpretation is central to detecting, diagnosing, and staging cancer and many other disorders. At a time when medical imaging is being transformed by digital technologies and artificial intelligence, understanding the basic perceptual and cognitive processes underlying medical image interpretation is vital for increasing diagnosticians’ accuracy and performance, improving patient outcomes, and reducing diagnostician burnout. Medical image perception remains substantially understudied. In September 2019, the National Cancer Institute convened a multidisciplinary panel of radiologists and pathologists together with researchers working in medical image perception and adjacent fields of cognition and perception for the “Cognition and Medical Image Perception Think Tank.” The Think Tank’s key objectives were to identify critical unsolved problems related to visual perception in pathology and radiology from the perspective of diagnosticians, discuss how these clinically relevant questions could be addressed through cognitive and perception research, identify barriers and solutions for transdisciplinary collaborations, define ways to elevate the profile of cognition and perception research within the medical image community, determine the greatest needs to advance medical image perception, and outline future goals and strategies to evaluate progress. The Think Tank emphasized diagnosticians’ perspectives as the crucial starting point for medical image perception research, with diagnosticians describing their interpretation process and identifying perceptual and cognitive problems that arise. This article reports the deliberations of the Think Tank participants to address these objectives and highlight opportunities to expand research on medical image perception.
Publisher: Center for Open Science
Date: 11-07-2017
Abstract: We describe and demonstrate an empirical strategy useful for discovering and replicating empirical effects in psychological science. The method involves the design of a meta-study, in which many independent experimental variables—that may be moderators of an empirical effect—are indiscriminately randomized. Radical randomization yields rich data sets that can be used to test the robustness of an empirical claim to some of the vagaries and idiosyncrasies of experimental protocols and enhances the generalizability of these claims. The strategy is made feasible by advances in hierarchical Bayesian modeling which allow for the pooling of information across unlike experiments and designs, and is proposed here as a gold standard for replication research and exploratory research. The practical feasibility of the strategy is demonstrated with a replication of a study on subliminal priming. All materials and data are freely available online via osf.io/u2vwa/.
No related grants have been discovered for Jennifer Trueblood.