完美主义结构研究述评

早期研究者如Adler、Homey和Ellis认为完美主义是一种单维的人格结构。后来的研究者如Hewitt、Frost等多持多维观点,认为完美主义是由不同因素组成的复杂结构。目前越来越多学者认同完美主义的二维观,认为完美主义有积极和消极之分。今后研究应考虑完美主义的文化因素,同时应从心理咨询、心理治疗和心理健康教育效果的角度来佐证某种结构观的合理性。     

A marginal maximum likelihood method for the vector threshold model to analyze dichotomous choice data

Abstract: At least two types of models, the vector model and the unfolding model can be used for the analysis of dichotomous choice data taken from, for example, the pick any/ n method. The previous vector threshold models have a difficulty with estimation of the nuisance parameters such as the individual vectors and thresholds. This paper proposes a new probabilistic vector threshold model, where, unlike the former vector models, the angle that defines an individual vector is a random variable, and where the marginal maximum likelihood estimation method using the expectation-maximization algorithm is adopted to avoid incidental parameters. The paper also attempts to discuss which of the two models is more appropriate to account for dichotomous choice data. Two sets of dichotomous choice data are analyzed by the model.     

基于双因子模型的测验总分和维度分的合成方法

双因子模型可以同时包含一个全局因子和多个局部因子,在描述多维测验结构时有其独特优势,近些年应用越来越广泛。文章基于双因子模型,提出了4种合成总分和维度分的方法,分别是:原始分法,加和法,全局题目加权加和法和局部题目加权加和法,并采用模拟的方法,在样本量、测验长度、维度间相关变化的条件下考察了这些方法与传统多维IRT方法的表现。最后,通过实证研究对结果进行了验证。结果显示:(1)全局加权加和法和局部加权加和法,尤其是局部加权加和法合成的总分和维度分与真值最接近、信度最高。(2)在维度间相关较高,测验长度较长的条件下,局部加权加和法的结果较好,部分条件下甚至优于多维IRT法。(3)仅有局部加权加和法合成的维度分能够反应维度间真实的相关关系。     

多维测验分数的报告与解释:基于双因子模型的视角

在心理、行为、管理和教育等社科领域,经常使用多维测验。本文评介并比较了各种多维测验的测量模型;总结了基于双因子模型计算得到的统计指标;根据不同研究目的,提出了两个兼顾简洁性和精确性的多维测验分析流程。作为例子,在马基雅维利主义人格量表的研究中,通过双因子模型分析了如何报告、解释多维测验分数以及如何利用多维建模进行后续分析。     

多维题组效应认知诊断模型

当前认知诊断领域还缺少对包含题组的测验进行诊断分析的研究, 即已开发的认知诊断模型无法合理有效地处理含有题组效应的测验数据, 且已开发的题组反应模型也不具有对被试知识结构或认知过程进行诊断的功能。针对该问题, 本文尝试性地将多维题组效应向量参数引入线性Logistic模型中, 同时开发了属性间具有补偿作用的和属性间具有非补偿作用的多维题组效应认知诊断模型。模拟研究结果显示新模型合理有效, 与线性Logistic模型和DINA模型对比研究后表明：(1)作答数据含有题组效应时, 忽略题组效应会导致项目参数的偏差估计并降低对目标属性的判准率; (2)新模型更具普适性, 即便当作答数据不存在题组效应时, 采用新模型进行测验分析亦能得到很好的项目参数估计结果且不影响对目标属性的判准率。整体来看, 新模型既具有认知诊断功能又可有效处理题组效应。     

测验链接中的锚题代表性研究

本文旨在以“锚题代表性”这一研究命题切入,探索在非等组锚测验设计下,作为实现测验链接的重要载体,锚题和相关的测验试卷/水平之间究竟应该有什么关系。本文首先指出锚题代表性这一概念在等值和垂直量尺化领域中具有不同的含义,并给出其在垂直量尺化中的含义。通过考察测验链接中有关锚题代表性的既有研究,系统总结相关研究成果,本文概括出了当前锚题构建实践的可能优化方案,分析了锚题代表性研究的未来方向。     

ConPar: a method for identifying groups of concordant subject proximity matrices for subsequent multidimensional scaling analyses

A common representation of data within the context of multidimensional scaling (MDS) is a collection of symmetric proximity (similarity or dissimilarity) matrices for each of M subjects. There are a number of possible alternatives for analyzing these data, which include: (a) conducting an MDS analysis on a single matrix obtained by pooling (averaging) the M subject matrices, (b) fitting a separate MDS structure for each of the M matrices, or (c) employing an individual differences MDS model. We discuss each of these approaches, and subsequently propose a straightforward new method (CONcordance PARtitioning—ConPar), which can be used to identify groups of individual-subject matrices with concordant proximity structures. This method collapses the three-way data into a subject×subject dissimilarity matrix, which is subsequently clustered using a branch-and-bound algorithm that minimizes partition diameter. Extensive Monte Carlo testing revealed that, when compared to K-means clustering of the proximity data, ConPar generally provided better recovery of the true subject cluster memberships. A demonstration using empirical three-way data is also provided to illustrate the efficacy of the proposed method.     

Psychophysics without physics: extension of Fechnerian scaling from continuous to discrete and discrete-continuous stimulus spaces

The computation of subjective (Fechnerian) distances from discrimination probabilities involves cumulation of appropriately transformed psychometric increments along smooth arcs (in continuous stimulus spaces) or chains of stimuli (in discrete spaces). In a space where any two stimuli that are each other's points of subjective equality are given identical physical labels, psychometric increments are positive differences ψ(x,y)-ψ(x,x) and ψ(y,x)-ψ(x,x), where x≠y and ψ is the probability of judging two stimuli different. In continuous stimulus spaces the appropriate monotone transformation of these increments (called overall psychometric transformation) is determined uniquely in the vicinity of zero, and its extension to larger values of its argument is immaterial. In discrete stimulus spaces, however, Fechnerian distances critically depend on this extension. We show that if overall psychometric transformation is assumed (A) to be the same for a sufficiently rich class of discrete stimulus spaces, (B) to ensure the validity of the Second Main Theorem of Fechnerian Scaling in this class of spaces, and (C) to agree in the vicinity of zero with one of the possible transformations in continuous spaces, then this transformation can only be identity. This result is generalized to the broad class of “discrete-continuous” stimulus spaces, of which continuous and discrete spaces are proper subclasses.     

Investigating the nature of expressiveness in stranger,acquaintance and intrafamilial homicides

This study explores the role of the victim–offender relationship in the dynamics of homicide, by examining the crime scene behaviour of 25 intrafamilial, 30 acquaintance and 27 stranger homicide offenders (n = 82). Six crime scene variables were examined: ‘Weapon from the scene’, ‘Excessive wounding’, ‘Facial trauma’, ‘Multiple wounds to a single area’, ‘Post‐mortem activity’ and ‘Manual violence’. The first objective was to identify whether these variables could be combined to form a partially ordered scale of expressiveness. The second was to examine whether the nature of this expressive crime scene varied according to the victim and offender relationship. It was hypothesised that the intrafamilial homicides would be characterised by a more expressive crime scene. This was examined by Partial Order Scalogram Analysis which supported the hypothesised link between the level of expressed emotion evident in the crime scene and the nature of the victim–offender relationship. Further analysis on the individual variables revealed that the best single predictor of the relationship between victim and offender was the presence of multiple wounding. These findings are discussed both as contributing to a theoretical understanding of the emotional salience of crime scene actions when killing a family member, and in practical terms in relation to the significance of these variables for both police investigations and clinical interventions with homicide perpetrators. Copyright © 2005 John Wiley & Sons, Ltd.