Response error and processing biases in confidence judgment

Previous studies showed that random error can explain overconfidence effects typically observed in the literature. One of these studies concluded that, after accounting for random error effects in the data, there is little support for cognitive‐processing biases in confidence elicitation. In this paper, we investigate more closely the random error explanation for overconfidence. We generated data from four models of confidence and then estimated the magnitude of random error in the data. Our results show that, in addition to the true magnitude of random error specified in the simulations, the error estimates are influenced by important cognitive‐processing biases in the confidence elicitation process. We found that random error in the response process can account for the degree of overconfidence found in calibration studies, even when that overconfidence is actually caused by other factors. Thus, the error models say little about whether cognitive biases are present in the confidence elicitation process. Copyright © 2008 John Wiley & Sons, Ltd.     

Attentional cueing induces false memory

The fluency of stimulus processing significantly contributes to recognition memory judgments. We investigated the effect of processing fluency induced by attentional cueing on recognition judgments. Participants performed a Remember/Know recognition test, while their spatial attention was manipulated in the test session. Stimulus location was either predicted (congruent condition) or unpredicted (incongruent condition) using an arrow cue. The results revealed that familiarity-based false recognition increased in the incongruent condition wherein the participants may have attributed part of the perceived disfluency to the attentional cue, and they may have overestimated the fluency for the stimulus, leading to increased false recognition. However, in the congruent condition, the participants may have attributed some parts of the perceived fluency to the attentional cue and underestimated the fluency for the stimulus, leading to decreased false recognition. In sum, stimulus-irrelevant attentional cueing induces unintentional processing about the source of fluency and biases recognition memory.     

The asymptotic posterior normality of the latent trait in an IRT model

It has long been part of the item response theory (IRT) folklore that under the usual empirical Bayes unidimensional IRT modeling approach, the posterior distribution of examinee ability given test response is approximately normal for a long test. Under very general and nonrestrictive nonparametric assumptions, we make this claim rigorous for a broad class of latent models.This research was partially supported by Office of Naval Research Cognitive and Neural Sciences Grant N0014-J-90-1940, 442-1548, National Science Foundation Mathematics Grant NSF-DMS-91-01436, and the National Center for Supercomputing Applications. We wish to thank Kumar Joag-dev and Zhiliang Ying for enlightening suggestions concerning the proof of the basic result.The authors wish to thank Kumar Joag-Dev, Brian Junker, Bert Green, Paul Holland, Robert Mislevy, and especially Zhiliang Ying for their useful comments and discussions.     

Themes in Therapist Development During the First Three Months of Clinical Experience

The results of a qualitative research study designed to better understand the developmental processes active in beginning therapists during the first three months of clinical contact is reported. Thirteen beginning therapists were asked to complete a monthly log describing experiences impacting their clinical work and themselves as therapists during their first three months of client contact. Data analysis revealed that the primary developmental theme active during this period of time is the development of therapist confidence. Two additional themes, the development of an internal gauge on which to evaluate current experiences and the development of boundaries around the self as a professional, were also found to be active during this time. These additional themes support the development of therapist confidence. Implications for training and research are identified.     

Application of the bootstrap methods in factor analysis

A Monte Carlo experiment is conducted to investigate the performance of the bootstrap methods in normal theory maximum likelihood factor analysis both when the distributional assumption is satisfied and unsatisfied. The parameters and their functions of interest include unrotated loadings, analytically rotated loadings, and unique variances. The results reveal that (a) bootstrap bias estimation performs sometimes poorly for factor loadings and nonstandardized unique variances; (b) bootstrap variance estimation performs well even when the distributional assumption is violated; (c) bootstrap confidence intervals based on the Studentized statistics are recommended; (d) if structural hypothesis about the population covariance matrix is taken into account then the bootstrap distribution of the normal theory likelihood ratio test statistic is close to the corresponding sampling distribution with slightly heavier right tail.This study was carried out in part under the ISM cooperative research program (91-ISM · CRP-85, 92-ISM · CRP-102). The authors would like to thank the editor and three reviewers for their helpful comments and suggestions which improved the quality of this paper considerably.     

Calibration of sensory and cognitive judgments: A single model for both

In a recent issue of this journal, Winman and Juslin (34 , 135–148, 1993) present a model of the calibration of subjective probability judgments for sensory discrimination tasks. They claim that the model predicts a pervasive underconfidence bias observed in such tasks, and present evidence from a training experiment that they interpret as supporting the notion that different models are needed to describe judgment of confidence in sensory and in cognitive tasks. The model is actually part of the more comprehensive decision variable partition model of subjective probability calibration that was originally proposed in Ferrell and McGoey (Organizational Behavior and Human Performance, 26 , 32–53, 1980). The characteristics of the model are described and it is demonstrated that the model does not predict underconfidence, that it is fully compatible with the overconfidence frequently found in calibration studies with cognitive tasks, and that it well represents experimental results from such studies. It is concluded that only a single model is needed for both types of task.     

海马CA_3区习得性LTP的进一步探讨

分辨学习中大鼠ＰＰ－ＣＡ_３突触效应有习得性ＬＴＰ产生,进一步观察到ＭＦ－ＣＡ_３及Ｃｏｍｍ－ＣＡ_３也同步地产生习得性ＬＴＰ,表明几种输入突触都产生习得性ＬＴＰ,而ＭＦ－ＣＡ_３突触效应增强的程度则较Ｃｏｍｍ－ＣＡ_３的为大（Ｐ＜０．０１）。海马ＣＡ_３注入印防己毒素能易化ＰＰ－ＣＡ_３突触习得性ＬＴＰ的产生,工作发现一侧海马ＣＡ_３注印防己毒素,易化对侧ＭＦ－ＣＡ_３突触习得性ＬＴＰ的产生,表明两侧海马ＣＡ_３区在其习得性ＬＴＰ的形成上是相互协同的。     

Verbal and nonverbal recognition memory in aphasic and nonaphasic stroke patients

The ability to retain lists of verbal and nonverbalizable items across recurrent recognition tasks was tested in three groups: (1) stroke patients with a left-brain lesion and aphasia, (2) stroke patients with a right-brain lesion and left hemiplegia, and (3) nonneurologically impaired outpatients. As determined with signal detection measures, aphasics were deficient in discriminating words that were to be remembered from those that were not; their recognition of nonverbal visual (geometric art) or auditory (bird calls) patterns, however, was unimpaired. Left hemiplegics showed the opposite pattern. After a long-term interval (<10 min), correct recognition of words was diminished in all groups whereas recognition of visual patterns increased. Both groups of stroke patients adopted material-specific decision criteria which in part accounted for the dissociation of verbal and nonverbal recognition memory by laterality of lesion. Item analysis indicated that aphasics' verbal memory difficulties were affected by acoustic-semantic confusion of list words.     

Parsing as a Cue-Based Retrieval Model

This paper develops a novel psycholinguistic parser and tests it against experimental and corpus reading data. The parser builds on the recent research into memory structures, which argues that memory retrieval is content-addressable and cue-based. It is shown that the theory of cue-based memory systems can be combined with transition-based parsing to produce a parser that, when combined with the cognitive architecture ACT-R, can model reading and predict online behavioral measures (reading times and regressions). The parser's modeling capacities are tested against self-paced reading experimental data (Grodner & Gibson, 2005), eye-tracking experimental data (Staub, 2011), and a self-paced reading corpus (Futrell et al., 2018).     

Choosing what to choose from: Preference for inclusion over exclusion when constructing consideration sets from large choice sets

Decision making is a two‐stage process, consisting of, first, consideration set construction and then final choice. Decision makers can form a consideration set from a choice set using one of two strategies: including the options they wish to further consider or excluding those they do not wish to further consider. The authors propose that decision makers have a relative preference for an inclusion (vs. exclusion) strategy when choosing from large choice sets and that this preference is driven primarily by a lay belief that inclusion requires less effort than exclusion, particularly in large choice sets. Study 1 demonstrates that decision makers prefer using an inclusion (vs. exclusion) strategy when faced with large choice sets. Study 2 replicates the effect of choice set size on preference for consideration set construction strategy and demonstrates that the belief that exclusion is more effortful mediates the relative preference for inclusion in large choice sets. Studies 3 and 4 further support the importance of perceived effort, demonstrating a greater preference for inclusion in large choice sets when decision makers are primed to think about effort (vs. accuracy; Study 3) and when the choice set is perceived as requiring more effort because of more information being presented about each alternative (vs. more alternatives in the choice set; Study 4). Finally, Study 5 manipulates consideration set construction strategy, showing that using inclusion (vs. exclusion) in large choice sets leads to smaller consideration sets, greater confidence in the decision process, and a higher quality consideration set.