融合反应时的多级评分IRT模型开发及其应用研究

当前大多数融合反应时的IRT模型仅适用于0-1评分数据资料,极大的限制了IRT反应时模型在实际中的应用。本文在传统的二级计分反应时IRT模型基础上,拟开发一种多级评分反应时模型。在层次建模框架下,分别采用拓广分部评分模型(GPCM)和对数正态模型构建融合反应时的多级评分IRT模型(本文记为JRT-GPCM),并采用全息贝叶斯MCMC算法实现新模型的参数估计。为验证新开发的JRT-GPCM模型的可行性及其在实践中的应用,本文开展了两项研究:研究1为模拟实验研究,研究2为新模型在大五人格-神经质分量表中的应用。研究1结果表明,JRT-GPCM模型的估计精度较高,且具有较好的稳健性。研究2表明,被试的潜在特质与作答速度具有一定的正相关,且本研究结果支持Ferrando和Lorenzo-Seva(2007)提出的“距离-困难度假设”,即当被试的潜在特质与项目的难度阈限距离越远,那么被试会花费更多的时间对项目进行作答。总之,本研究为拓展反应时信息在心理测量及教育中的应用提供新的方法支持。     

管理胜任力特征分析:结构方程模型检验

管理胜任力特征分析是人事选拔与评价的重要内容之一。本研究在运用基于胜任力的职位分析并总结国内外有关文献的基础上,编制了管理综合素质评价量表,并运用此量表调查了220名中高层管理者,采用因素分析和结构方程模型检验企业高级管理者胜任力特征的结构。结果表明,管理胜任力特征结构由管理素质和管理技能等两个维度构成,但在维度要素及其关键度上,职位层次间存在显著差异。本研究为管理职位的测评选拔提供了新的理论依据。     

Empirical underidentification in estimating random utility models: The role of choice sets and standardizations

A standard approach to distinguishing people’s risk preferences is to estimate a random utility model using a power utility function to characterize the preferences and a logit function to capture choice consistency. We demonstrate that with often-used choice situations, this model suffers from empirical underidentification, meaning that parameters cannot be estimated precisely. With simulations of estimation accuracy and Kullback–Leibler divergence measures we examined factors that potentially mitigate this problem. First, using a choice set that guarantees a switch in the utility order between two risky gambles in the range of plausible values leads to higher estimation accuracy than randomly created choice sets or the purpose-built choice sets common in the literature. Second, parameter estimates are regularly correlated, which contributes to empirical underidentification. Examining standardizations of the utility scale, we show that they mitigate this correlation and additionally improve the estimation accuracy for choice consistency. Yet, they can have detrimental effects on the estimation accuracy of risk preference. Finally, we also show how repeated versus distinct choice sets and an increase in observations affect estimation accuracy. Together, these results should help researchers make informed design choices to estimate parameters in the random utility model more precisely.     

辱虐管理的应对：基于人际拒绝的多动力模型分析

随着辱虐管理产生破坏性影响的作用机制不断得到丰富和完善, 受辱虐下属选择特定应对方式的原因以及有效性成为未来辱虐管理的研究方向。基于人际拒绝的多动力模型, 梳理了在不同质量LMX的关系情境中受辱虐下属的应对方式, 并提出特定应对方式可能引起辱虐管理的恶性循环的假设模型。建议未来研究通过丰富下属的应对行为变量、增加人格和环境的调节机制以完善受辱虐下属的应对模型, 并以此为基础探究辱虐管理的消极互动机制, 为打破辱虐管理恶性循环提供理论支持。     

基因-环境交互作用理论模型及其检验方法

素质?压力模型、不同易感性模型和优势敏感性模型是当前有关基因?环境交互作用的三种代表性理论模型。素质?压力模型认为“近墨者黑”或“出淤泥而不染”, 优势反应敏感性模型认为“近朱者赤”, 而不同易感性模型则兼收并蓄, 认为某些个体近墨则黑, 近朱则赤。检验上述模型的现实有效性是当前基因?环境交互作用研究领域的热点问题之一。概观而言, 分组回归和分层回归是常用的传统检验方法, 显著性区域分析法和新参数回归模型法则是新近兴起的。未来研究需要进一步探索三种模型的领域特殊性、种族差异等问题, 检验这些模型的方法也有待改善。     

Every Finitely Reducible Logic has the Finite Model Property with Respect to the Class of ♦-Formulae

In this paper a unified framework for dealing with a broad family of propositional multimodal logics is developed. The key tools for presentation of the logics are the notions of closure relation operation and monotonous relation operation. The two classes of logics: FiRe-logics (finitely reducible logics) and LaFiRe-logics (FiRe-logics with local agreement of accessibility relations) are introduced within the proposed framework. Further classes of logics can be handled indirectly by means of suitable translations. It is shown that the logics from these classes have the finite model property with respect to the class of -formulae, i.e. each -formula has a -model iff it has a finite -model. Roughly speaking, a -formula is logically equivalent to a formula in negative normal form without occurrences of modal operators with necessity force. In the proof we introduce a substantial modification of Claudio Cerrato's filtration technique that has been originally designed for graded modal logics. The main core of the proof consists in building adequate restrictions of models while preserving the semantics of the operators used to build terms indexing the modal operators.     

The hoarding dimension of OCD: psychological comorbidity and the five-factor personality model

Although hoarding has been associated with several psychological disorders, it is most frequently linked to obsessive-compulsive disorder (OCD). The present study assessed hoarding obsessions and compulsions in 204 individuals with OCD, and evaluated how hoarding was related to obsessive-compulsive symptom severity, psychological comorbidity, and personality as measured by the five-factor model. Results indicated that hoarding in OCD is a dimensional variable that is positively associated with dysphoria, total number of lifetime Axis I disorders, and lifetime histories of bipolar I, PTSD, and body dysmorphic disorder. Hoarding was negatively correlated with the NEO-Personality Inventory-Revised (NEO-PI-R) factor of Conscientiousness and positively associated with the NEO-PI-R factor of Neuroticism. When all personality and psychopathology variables were entered into a regression equation, dysphoria, bipolar II disorder, Conscientiousness, age, and Extraversion emerged as significant predictors of hoarding severity. Recommendations are made for clinicians and for future research.     

Event-related fMRI of category learning: differences in classification and feedback networks

Eighteen healthy young adults underwent event-related (ER) functional magnetic resonance imaging (fMRI) of the brain while performing a visual category learning task. The specific category learning task required subjects to extract the rules that guide classification of quasi-random patterns of dots into categories. Following each classification choice, visual feedback was presented. The average hemodynamic response was calculated across the eighteen subjects to identify the separate networks associated with both classification and feedback. Random-effects analyses identified the different networks implicated during the classification and feedback phases of each trial. The regions included prefrontal cortex, frontal eye fields, supplementary motor and eye fields, thalamus, caudate, superior and inferior parietal lobules, and areas within visual cortex. The differences between classification and feedback were identified as (i) overall higher volumes and signal intensities during classification as compared to feedback, (ii) involvement of the thalamus and superior parietal regions during the classification phase of each trial, and (iii) differential involvement of the caudate head during feedback. The effects of learning were then evaluated for both classification and feedback. Early in learning, subjects showed increased activation in the hippocampal regions during classification and activation in the heads of the caudate nuclei during the corresponding feedback phases. The findings suggest that early stages of prototype-distortion learning are characterized by networks previously associated with strategies of explicit memory and hypothesis testing. However as learning progresses the networks change. This finding suggests that the cognitive strategies also change during prototype-distortion learning.     

Decision making and confidence given uncertain advice

We study human decision making in a simple forced-choice task that manipulates the frequency and accuracy of available information. Empirically, we find that people make decisions consistent with the advice provided, but that their subjective confidence in their decisions shows 2 interesting properties. First, people's confidence does not depend solely on the accuracy of the advice. Rather, confidence seems to be influenced by both the frequency and accuracy of the advice. Second, people are less confident in their guessed decisions when they have to make relatively more of them. Theoretically, we develop and evaluate a type of sequential sampling process model—known as a self-regulating accumulator—that accounts for both decision making and confidence. The model captures the regularities in people's behavior with interpretable parameter values, and we show its ability to fit the data is not due to excessive model complexity. Using the model, we draw conclusions about some properties of human reasoning under uncertainty.