On the evaluation of one-sided evidence

We examine predictions and judgments of confidence based on one-sided evidence. Some subjects saw arguments for only one side of a legal dispute while other subjects (called ‘jurors’) saw arguments for both sides. Subjects predicted the number of jurors who favored the plaintiff in each case. Subjects who saw only one side made predictions that were biased in favor of that side. Furthermore, they were more confident but generally less accurate than subjects who saw both sides. The results indicate that people do not compensate sufficiently for missing information even when it is painfully obvious that the information available to them is incomplete. A simple manipulation that required subjects to evaluate the relative strength of the opponent's side greatly reduced the tendency to underweigh missing evidence.     

Confidence and Uncertainty in Judgmental Forecasting: Differential Effects of Scenario Presentation

Multiple scenario analysis is used by many organizations for long-term planning, in part because the development of more than one scenario of the future is thought to prevent overconfidence in any one specific forecast. The present study attempts to clarify some of the questions concerning the cognitive effects of scenario presentation by distinguishing between confidence and subjective uncertainty. It examined the impact of different types of scenario information on confidence ratings, credible intervals, and features of forecast series. Subjects (N=186) read either one, two, or no scenario(s) describing potential changes in the level of a stimulus variable, then made forecasts of that variable over the next fifty years. Reading any type of scenario information increased confidence in forecasts; there was no reduction in confidence due to presentation of multiple conflicting scenarios, compared to presentation of only one scenario. Differences in number and in type of scenarios presented did, however, affect subjective uncertainty.     

Interval estimation for linear functions of medians in within-subjects and mixed designs

The currently available distribution-free confidence interval for a difference of medians in a within-subjects design requires an unrealistic assumption of identical distribution shapes. A confidence interval for a general linear function of medians is proposed for within-subjects designs that do not assume identical distribution shapes. The proposed method can be combined with a method for linear functions of independent medians to provide a confidence interval for a linear function of medians in mixed designs. Simulation results show that the proposed methods have good small-sample properties under a wide range of conditions. The proposed methods are illustrated with examples, and R functions that implement the new methods are provided.     

Image-size disparity reduces difference detection in face matching

Face matching is the act of deciding whether two facial images depict the same person or different people. The real-world face-matching task of checking photo IDs typically occurs under conditions of image-size disparity: A small picture is compared with a life-size face. We examined the effect of image-size disparity on face-matching accuracy. In three experiments, subjects were presented with pairs of equivalently or disparately sized images that depicted the same person or different people. Subjects made same/different judgments and, in two experiments, also reported confidence. Difference detection was significantly poorer given disparate (versus equivalent) image size. Confidence was significantly higher when responses were correct versus incorrect. These findings held whether viewing and decision time was unlimited or limited. Our results raise the practical concern that image-size disparity may undermine difference detection in ID checking, while also indicating that people have some insight into the accuracy of their face-matching judgments.     

How do we judge our confidence? Differential effects of meta-memory feedback on eyewitness accuracy and confidence

According to the cue–belief model, we assess confidence in our memories using self-credibility cues that reflect beliefs about our memory faculties. We tested the influence of meta-memory feedback on self-credibility cues in the context of eyewitness testimony, when feedback was provided prior to “testifying” via a memory questionnaire (Experiment 1) and after an initial memory questionnaire but before participants had to retake it (Experiment 2). Participants received feedback (good score, bad score, or none) on a fictitious scale purported to predict eyewitness memory ability. Those given good score feedback before testifying were more confident (but no more accurate) than those given bad score feedback. Feedback also affected confidence (good increased and bad decreased) and accuracy (good increased) after testifying but only on leading questions. These differential effects of meta-memory feedback on confidence for normal and leading questions are not explained by the cue–belief model. Implications for our confidence judgments are discussed.     

元认知中自信心对联合决策的预测作用

元认知通常指个体对自身认知活动的主观判断, 自信心作为其指标之一, 对个体认识和调节自己的行为有重要作用。研究表明自信心指标在联合研究过程中常见的任务类型涉及基础和高级心理加工过程, 此外, 自信心对联合决策的预测逐渐向基于计算模型的探索性参数变化。最后, 自信心的神经生理研究发现了前额叶皮层及其相关脑区和后顶叶皮层的重要性。今后应注重探索可能的预测参数和模型, 优化自信心对联合决策的预测作用。     

Algebras of Intervals and a Logic of Conditional Assertions

Intervals in boolean algebras enter into the study of conditional assertions (or events) in two ways: directly, either from intuitive arguments or from Goodman, Nguyen and Walker's representation theorem, as suitable mathematical entities to bear conditional probabilities, or indirectly, via a representation theorem for the family of algebras associated with de Finetti's three-valued logic of conditional assertions/events. Further representation theorems forge a connection with rough sets. The representation theorems and an equivalent of the boolean prime ideal theorem yield an algebraic completeness theorem for the three-valued logic. This in turn leads to a Henkin-style completeness theorem. Adequacy with respect to a family of Kripke models for de Finetti's logic, ukasiewicz's three-valued logic and Priest's Logic of Paradox is demonstrated. The extension to first-order yields a short proof of adequacy for Körner's logic of inexact predicates.