单维项目因素分析：CCFA与IRT估计方法的比较

当观测指标变量为二分分类数据时,传统的因素分析方法不再适用。作者简要回顾了SEM框架下的分类数据因素分析模型和IRT框架下的测验题目和潜在能力的关系模型,并对两种框架下主要采用的参数估计方法进行了总结。通过两个模拟研究,比较了SEM框架下GLSc和MGLSc估计方法与IRT框架下MML/EM估计方法的差异。研究结果表明：（1）三种方法中,GLSc得到参数估计的偏差最大,MGLSc和MML/EM估计方法相差不大;（2）随着样本量增大,各种项目参数估计的精度均提高;（3）项目因素载荷和难度估计的精度受测验长度的影响;（4）项目因素载荷和区分度估计的精度受总体因素载荷（区分度）高低的影响;（5）测验项目中阈值的分布会影响参数估计的精度,其中受影响最大的是项目区分度。（6）总体来看,SEM框架下的项目参数估计精度较IRT框架下项目参数估计的精度高。此外,文章还将两种方法在实际应用中应该注意的问题提供了一些建议。     

Assessing local influence for specific restricted likelihood: Application to factor analysis

In restricted statistical models, since the first derivatives of the likelihood displacement are often nonzero, the commonly adopted formulation for local influence analysis is not appropriate. However, there are two kinds of model restrictions in which the first derivatives of the likelihood displacement are still zero. General formulas for assessing local influence under these restrictions are derived and applied to factor analysis as the usually used restriction in factor analysis satisfies the conditions. Various influence schemes are introduced and a comparison to the influence function approach is discussed. It is also shown that local influence for factor analysis is invariant to the scale of the data and is independent of the rotation of the factor loadings. The authors are most grateful to the referees, the Associate Editor, and the Editor for helpful suggestions for improving the clarity of the paper.     

项目反应理论多级记分模型参数估计的实现

项目反应理论中参数估计程序的实现,一直是研究现代测量理论的学者们关注的问题。该研究从理论上探讨了多级模型参数估计的实现途径,并模拟了5批不同数量及分布情形的项目及被试参数,生成相应的原始得分矩阵,对自编程序及国际流行的相关程序进行了严格的比较校验,验证结果证明本程序具有精确、稳定的性能,并且发现被试量太少将影响参数估计的精确性及稳定性     

The emergence of personality: Dynamic foundations of individual variation

We conceptualize personality and individual variation from the perspective of dynamical systems. People’s thoughts, feelings, and predispositions for action are inherently dynamic, displaying constant change due to internal mechanisms and external forces, but over time the flow of thought and action converges on a narrow range of states—a fixed-point attractor—that provides cognitive, affective, and behavioral stability. An attractor for personal dynamics develops through two mechanisms: the synchronization of individuals’ internal states in social interaction, and the self-organization of thoughts and feelings with respect to a higher-order property (e.g., goal, self-concept). We present formal models of both processes and instantiate each in computer simulations. Discussion centers on the implications of interpersonal synchronization and self-organization dynamics for issues in personality psychology, including shared vs. non-shared environmental influences on personality development, the expression of personality in social interaction, personal stability vs. change, personal vs. situational causation, and the emergence of self-concept.     

Statistical models of syntax learning and use

This paper shows how to define probability distributions over linguistically realistic syntactic structures in a way that permits us to define language learning and language comprehension as statistical problems. We demonstrate our approach using lexical‐functional grammar (LFG), but our approach generalizes to virtually any linguistic theory. Our probabilistic models are maximum entropy models. In this paper we concentrate on statistical inference procedures for learning the parameters that define these probability distributions. We point out some of the practical problems that make straightforward ways of estimating these distributions infeasible, and develop a “pseudo‐likelihood” estimation procedure that overcomes some of these problems. This method raises interesting questions concerning the nature of the data available to a language learner and the modularity of language learning and processing.     

项目反应理论等级反应模型项目信息量

信息函数作为项目反应理论中的一个重要概念,在进行项目和测验分析的工作中,以及在指导测验编制的工作中,有着非常重要的应用价值。信息函数的应用在计算机化自适应测验中更是重中之重,也受到最大关注。然而,关于多级记分项目信息函数特性的研究还比较少。本研究模拟了被试特质水平参数数据和项目参数数据,其中被试特质水平参数生成了121个被试特质水平参数点,项目参数生成了4批不同区分度参数数据,每批数据有126个不同难度等级参数组合模式的项目,每个项目有5个难度等级。通过数据分析后发现,等级反应模型项目提供最大信息量所对应的被试特质水平,是与该项目几个相互临近的难度等级组相适应,既不是只与其中一个难度等级对应,也不一定是与所有难度等级对应。本研究称这种规律为“临近难度等级占优”。这个发现无疑对测验质量分析和测验编制工作,包括计算机化自适应测验编制,具有重要的指导意义     

Recovering a Probabilistic Knowledge Structure by Constraining its Parameter Space

In the Basic Local Independence Model (BLIM) of Doignon and Falmagne (Knowledge Spaces, Springer, Berlin, 1999), the probabilistic relationship between the latent knowledge states and the observable response patterns is established by the introduction of a pair of parameters for each of the problems: a lucky guess probability and a careless error probability. In estimating the parameters of the BLIM with an empirical data set, it is desirable that such probabilities remain reasonably small. A special case of the BLIM is proposed where the parameter space of such probabilities is constrained. A simulation study shows that the constrained BLIM is more effective than the unconstrained one, in recovering a probabilistic knowledge structure.     

计算机适应性测验条件下认知设计项目预测参数的影响

自动化项目生成(Automatic Item Generation)中的项目参数是基于认知项目设计的刺激特征集预测的, 在不确定性来源上较之用经验数据标定的参数更为复杂。文章通过实证研究分析了在计算机适应性测验条件下基于认知设计系统法生成的抽象推理测验(ART)项目预测参数对能力参数估计的精确性。研究表明, 项目预测参数比相应标定参数分布更为趋中。这种回归效应既影响到能力参数估计误差大小, 也导致适应性测验过程中项目选择的差异。在控制了项目选择差异之后, 能力参数估计误差较之基于项目标定参数的能力估计误差大, 但差别并不明显。两者相应的能力估计值相关很高, 对应能力值之间的差异很小, 且几乎贯彻整个能力分布区间。