共情对广义互惠的影响：自我-他人重叠的中介作用

与“我帮你,你帮我”的直接互惠相比,“我帮你,你帮他”的积极广义互惠,促使受助者转变为助人者帮助更多的人。与之相反,“我伤你,你伤他”的消极广义互惠,易导致受害者转变为伤害者波及无辜他人。以往研究未探寻到既能促进积极广义互惠,又能抑制消极广义互惠的因素。采用两阶段独裁者博弈任务范式,通过两项实验发现,共情是一个能够起到扩大积极广义互惠传递效应并削弱消极广义互惠传递效应双重作用的特殊变量,其机制在于自我-他人重叠,支持了自我扩张模型。这一研究为营造良好社会道德氛围,加强公民道德建设,保障公正和谐的社会环境提供了思路。     

Stopping rules for multi-category computerized classification testing

Computerized classification testing (CCT) aims to classify persons into one of two or more possible categories to make decisions such as mastery/non-mastery or meet most/meet all/exceed. A defining feature of CCT is its stopping criterion: the test terminates when there is enough confidence to make a decision. There is abundant research on CCT with a single cut-off, and two common stopping criteria are the sequential probability ratio test (SPRT) statistic and the generalized likelihood ratio statistic (GLR). However, there is a relative scarcity of research extending the SPRT to the multi-hypothesis case for when there is more than one cut-off. In this paper, we propose a new multi-category GLR (mGLR) statistic as well as a stochastically curtailed version of the CCT with three or more categories. A simulation study was conducted to show that the mGLR statistic outperformed the existing stopping rules by generating shorter average test length without sacrificing classification accuracy. Results also revealed that the stochastically curtailed mGLR successfully increased test efficiency in certain testing conditions.     

Information Processing and Decision-Making in Pathological Worriers and their Potential Role in Mechanisms of Generalized Anxiety Disorder

Systematic information processing and decision-making under uncertainty are key constructs of new conceptions explaining the severity of pathological worry. The current study attempted to analyze their usefulness in subclinical and clinical groups. In the first phase of the study (N = 251) participants were examined with the Penn State Worry Questionnaire (PSWQ), a GP consultationrelated survey, and a screening survey for generalized anxiety disorder (GAD). In the second phase (N = 220), the State-Trait Anxiety Inventory, the PSWQ, and tasks measuring systematic information processing (SIP) versus heuristic reasoning (HR) were applied. In the third phase (N = 60), GAD (n = 30) and healthy control (n = 30) groups were examined with the above methods and the Iowa Gambling Task (IGT). In the low risk group, a relationship between mood and the representativeness heuristic (ρ = 0.50), as well as anchoring and adjustment heuristic (anxiety-related stimuli) was found (ρ = −0.53). In the GAD group, significant correlations between the PSWQ score, the IGT loss avoidance score (ρ = 0.40), and total IGT score (ρ = 0.48) were found. The results did not confirm a particular usefulness of the systematic/heuristic information processing construct in subclinical and clinical groups. Theory-consistent results were rather found in the nonclinical groups. Nevertheless, the data revealed some interesting findings supporting potential explanatory power of some theoretical models.     

Out-of-bag Prediction Error: A Cross Validation Index for Generalized Structured Component Analysis

Cross validation is a useful way of comparing predictive generalizability of theoretically plausible a priori models in structural equation modeling (SEM). A number of overall or local cross validation indices have been proposed for existing factor-based and component-based approaches to SEM, including covariance structure analysis and partial least squares path modeling. However, there is no such cross validation index available for generalized structured component analysis (GSCA) which is another component-based approach. We thus propose a cross validation index for GSCA, called Out-of-bag Prediction Error (OPE), which estimates the expected prediction error of a model over replications of so-called in-bag and out-of-bag samples constructed through the implementation of the bootstrap method. The calculation of this index is well-suited to the estimation procedure of GSCA, which uses the bootstrap method to obtain the standard errors or confidence intervals of parameter estimates. We empirically evaluate the performance of the proposed index through the analyses of both simulated and real data.     

Differential Effects of Right‐Wing Authoritarianism and Social Dominance Orientation on Dimensions of Generalized Prejudice in Brazil

Previous research within a dual‐process cognitive‐motivational theory of ideology and prejudice has indicated that dimensions of generalized prejudice are structured around attitudes towards dangerous, derogated and dissident groups, and that these prejudice dimensions are differentially predicted by the ideological attitudes of Right‐Wing Authoritarianism (RWA) and Social Dominance Orientation (SDO). However, to date, these findings have been restricted to New Zealand samples. We describe two studies examining whether the structure of prejudiced attitudes and the differential prediction by RWA and SDO replicate in the Brazilian context, incorporating context‐relevant examples of each group—politicians, those from the northeast region of Brazil, and environmentalists. Results broadly supported the three‐factor structure of dangerous, derogated, and dissident groups. Consistent with previous research, regression and structural equation analyses showed that RWA explained prejudice against dangerous groups, SDO explained prejudice against derogated groups, and both RWA and SDO explained prejudice against dissident groups. This research provides some evidence for the generalizability of the three‐dimensional structure of generalized prejudice and differential prediction by RWA and SDO. Copyright © 2014 European Association of Personality Psychology     

变长CD-CAT中的曝光控制与终止规则

本研究借鉴传统计算机化自适应测验的思想, 并结合认知诊断的特点, 在认知诊断框架下提出了4种变长CD-CAT的终止规则, 分别是属性标准误法(SEA)、邻近后验概率之差法(DAPP)、二等分法(HA)以及混合法(HM)。在未控制曝光和采用不同曝光控制条件下, 与HSU法及KL法进行了比较。研究结果表明：(1) 终止条件越严格, 平均测验长度越长, 按测验长度最大值终止的测验百分比越大, 模式判准率越高。(2) 当未加入曝光控制时, 4种新的终止规则均有较好表现, 与HSU法十分接近。随着最大后验概率预设值的增加或e的减小, 模式判准率呈上升趋势, 平均测验长度逐渐增加, 但在题库使用率方面均较差。(3) 当加入项目曝光控制时, 6种变长终止规则下的题库使用率有了极大的提升, 仍能保持较高的模式判准率, 并且不同的曝光控制方法对终止规则的影响是不同的。其中, 相对标准终止规则极易受到曝光控制方法的影响。(4) 综合来看, SEA、HM以及HA法在各项指标上的表现与HSU法基本一致, 其次为KL法和DAPP法。     

A general proof of consistency of heuristic classification for cognitive diagnosis models

The Asymptotic Classification Theory of Cognitive Diagnosis (Chiu et al., 2009, Psychometrika, 74, 633–665) determined the conditions that cognitive diagnosis models must satisfy so that the correct assignment of examinees to proficiency classes is guaranteed when non‐parametric classification methods are used. These conditions have only been proven for the Deterministic Input Noisy Output AND gate model. For other cognitive diagnosis models, no theoretical legitimization exists for using non‐parametric classification techniques for assigning examinees to proficiency classes. The specific statistical properties of different cognitive diagnosis models require tailored proofs of the conditions of the Asymptotic Classification Theory of Cognitive Diagnosis for each individual model – a tedious undertaking in light of the numerous models presented in the literature. In this paper a different way is presented to address this task. The unified mathematical framework of general cognitive diagnosis models is used as a theoretical basis for a general proof that under mild regularity conditions any cognitive diagnosis model is covered by the Asymptotic Classification Theory of Cognitive Diagnosis.     

使用似然比D2统计量的题目属性定义方法

题目属性的定义是实施认知诊断评价的关键步骤, 通过有丰富经验的领域专家对题目的属性进行定义是当前的主要方法, 然而该方法受到许多主观经验因素的影响。寻找客观的题目属性定义或验证方法可以为主观定义过程提供策略支持或对结果进行改进, 因此已经引起研究者们的关注。本研究构建了一种简单高效的题目属性定义方法, 研究使用似然比D2统计量从作答数据中估计题目属性的方法, 实现属性掌握模式、题目参数和题目属性向量的联合估计。模拟研究结果表明, 使用似然比D2统计量可以有效地识别题目的属性向量, 该方法一方面可以实现新编制题目属性向量的在线估计, 另一方面可以验证已经定义的题目属性向量的准确性。     

Effectiveness of the Hamilton Anxiety Rating Scale with Older Generalized Anxiety Disorder Patients

To expand the collection of instruments available for assessment of anxiety in the elderly, this report examined the original and revised Hamilton anxiety scales in a sample of 50 older adults diagnosed with Generalized Anxiety Disorder (GAD) and 93 normal community participants (ages 55–82). Although the revised anxiety scale had better discriminant validity (lower correlation with the revised Hamilton depression scale) than the original anxiety and depression scales, a considerable amount of shared variance still existed (41% shared variance, GAD sample alone; 17% control sample alone; 74% shared variance, both samples combined). Near-perfect group classification was possible using 7 items from the original anxiety scale and 10 items from the revised anxiety scale. Results are discussed in light of their implications for use of the Hamilton anxiety rating scale with older anxiety-disordered patients.