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.     

Millon Clinical Multiaxial Inventory (MCMI) computer-generated diagnoses: How do they compare to clinician judgment?

During the past several decades, computers have achieved increasing prominence in psychological assessment procedures. This is particularly true for computer-based test interpretation and diagnosis. This study reports on a study designed to compare the accuracy of computer-based diagnoses with clinician-generated diagnoses. The Millon Clinical Multiaxial Inventory (MCMI) was administered to 151 consecutively admitted inpatients at a large private psychiatric hospital. The computer-generated diagnoses were compared with those generated by admitting psychiatrists. The results indicated that the MCMI diagnostic impressions underestimated the severity of depressive disorders when compared with clinician diagnoses on Axis I. Specifically, clinicians diagnosed major depression much more frequently than did the MCMI. In addition, clinicians diagnosed anxiety disorders much less frequently than did the MCMI.     

An evaluation of the reliability of probability judgments across response modes and over time

Despite the importance of probability assessment methods in behavioral decision theory and decision analysis, little attention has been directed at evaluating their reliability and validity. In fact, no comprehensive study of reliability has been undertaken. Since reliability is a necessary condition for validity, this oversight is significant. The present study was motivated by that oversight. We investigated the reliability of probability measures derived from three response modes: numerical probabilities, pie diagrams, and odds. Unlike previous studies, the experiment was designed to distinguish systematic deviations in probability judgments, such as those due to experience or practice, from random deviations. It was found that subjects assessed probabilities reliably for all three assessment methods regardless of the reliability measures employed. However, a small but statistically significant decrease over time in the magnitudes of assessed probabilities was observed. This effect was linked to a decrease in subjects overconfidence during the course of the experiment.     

Upward versus Downward Anchoring in Frequency Judgments of Social Facts

Frequency estimation of social facts in two methods of judgment elicitation was investigated. In the “narrow-range” condition, subjects answered questions in the format: “Out of 100 incidents, how many belong to category X?” In the “wide-range” condition, the frequency for the same event was assessed with respect to “Out of 10,000”. Judged frequencies in the wide-range condition were divided by 100, and were compared with the corresponding judgments in the narrow-range condition. Such comparisons were made for low-frequency and high-frequency events. Previous research has shown that, for low-frequency events, judged frequencies are proportionally greater in the narrow-range than in the wide-range condition. These results reflect cognitive processes of implicit anchoring, whereby judged frequencies lie close to small numbers within the response ranges provided. I call this process “downward anchoring,” and predicted that this tendency would be replicated in the present study. Moreover, I predicted that assessments about high-frequency events would evoke similar cognitive processes operating in the opposite direction. By such “upward anchoring,” judged frequencies would lie close to relatively larger numbers within the given response ranges. Consequently, I predicted that judged frequencies for high-frequency events would be proportionally greater in the wide-range condition than in the narrow-range condition. These predictions were confirmed.     

Reflections on segregating and assessing areas of competence

Various complexities that arise in the application of legal and/or clinical criteria to the actual assessment of competence/capacity are discussed, and a particular way of understanding the nature of such criteria is recommended.     

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.     

时序信息提取机制的探索

对时序信息加工的经典研究是采用新近性判断范型,结果发现其提取机制是以新近性为基础的逆向串行搜索过程。本研究采用新近性判断范型和早远性判断范型对时序信息的提取机制进行了深入的考察,结果表明：（ｌ）提取时序信息既存在逆向串行搜索,又存在顺向串行搜索;（２）早远性判断和新近性判断任务对不同部分时序信息恢复的效应不同,其中早远性判断易化早远部分,新近性判断易化新近部分──表现为对相应部分辨别力的提高和正确反应潜伏期的缩短;（３）在不同的时序信息提取任务中,被试会根据具体条件进行反转反应。     

语音信息对不同水平中国英语学习者语义加工的影响

研究通过同音异义词对被试判断句子语义正误的干扰实验,来考查语音信息对不同英语水平的中国英语学习者语义加工的影响。实验结果发现,英语水平较高的中国被试所受到的同音异义词的干扰较大,而英语水平普通的被试受到的干扰很小。这一结果说明,英语学习者的水平越高,其语音信息的使用程度越高。     

词频和年级对FOK判断的影响

本实验以识记材料的词频高低和被试年级为自变量对被试元记忆监测的FOK(feeling of knowing)判断进行研究。实验采用Hart提出的RJR(回忆—FOK判断—标准测验 )的经典范式。结果表明 :被试的年级影响FOK判断等级和准确性 ,大学生的FOK判断等级和准确性均高于高一年级学生 ;识记材料词频影响FOK判断等级的高低 ,不影响FOK判断准确性 ,被试对高频词对的FOK判断等级高于对低频词对的FOK判断等级 ,但FOK判断准确性无明显差异。     

道德外语效应及其调节变量：来自元分析的证据

同一个道德决策情景使用外语(相比母语)呈现时,个体会表现出更强的功利性倾向,即道德外语效应。随着研究的深入,结论并不一致。本研究运用元分析方法首次探讨了语言类型(母语vs.外语)对道德判断中功利性倾向的影响,并分析了相关的调节变量。通过文献检索及梳理,共有19篇文献46个独立样本97个效应量符合元分析标准(N=9672)。结果显示存在较小但稳定的道德外语效应(g=0.23);调节效应分析表明,道德外语效应受故事类型的影响,在个人道德两难故事中存在较小但稳定的外语效应(g=0.32),但在非个人道德两难故事(g=0.11)与日常道德评价故事中(g=0.12)不存在外语效应;非个人道德两难故事中的外语效应受记分方式的影响,多点记分在该故事类型下存在效应(g=0.27),二点记分不存在效应(g=0.05);性别和语系类型没有显著的调节效应。这些结果表明语言类型对个体面对道德困境时的选择倾向有一定程度的影响,道德故事类型和记分方式在未来的研究中需要加以考虑。