场景知觉中的眼动分析指标:基于注视和眼跳视角

眼动范式是场景知觉研究的重要方法之一,可以通过对场景知觉过程中眼动变化的实时记录,真实地反映场景信息加工的内在心理机制;然而,人们的心理活动是极其复杂的,与之相应的眼动指标也具有多样性和复杂性。对眼动指标的分析,有不同的分析维度,比如整体和局部、时间和空间等。本文回顾了已有的眼动指标分类,并尝试从注视和眼跳的视角对场景知觉过程中的眼动指标进行分类。在此基础上,从界定标准、心理学意义、研究应用等方面对相应的眼动指标进行分析和介绍,最后提出了眼动指标分析和应用可能存在的问题,以及未来研究可能拓展的领域。     

潜变量交互效应结构方程：分布分析方法

对于潜变量交互效应结构方程分析,目前应用较多的是乘积指标方法.分布分析方法国内还罕有应用,包括潜调节结构方程（LMS）方法和准极大似然（QML）方法.该研究以乘积指标方法的模型假设为参照,介绍了分布分析方法的模型假设.并简要叙述了LMS方法及其Mplus程序,QML方法及其QML程序.综合现有研究结果,总结出LMS和QML方法、无约束和约束方法的特点,从中可以看出各方法的优缺点,推荐了不同条件下合适的分析方法.     

潜变量交互效应建模: 告别均值结构

潜变量交互效应建模研究近年来有了长足的发展, 但模型中被认为不可缺少的均值结构往往让实际应用工作者却步。本文首先分析了潜变量交互效应模型中均值结构产生的根源; 然后讨论了指标变换与均值结构的关系; 接着提出了一个均值为零的潜变量交互结构, 所建立的模型不需要均值结构, 却不会改变主效应和交互效应等参数; 最后用模拟例子对无均值结构和有均值结构的两种模型的参数估计进行了比较, 结果符合理论预期, 困扰人们多年的均值结构问题从此可以终结。     

Nonparametric item response theory axioms and properties under nonlinearity and their exemplification with knowledge space theory

This paper investigates the dichotomous Mokken nonparametric item response theory (IRT) axioms and properties under incomparabilities among latent trait values and items. Generalized equivalents of the unidimensional nonparametric IRT axioms and properties are formulated for nonlinear (quasi-ordered) person and indicator spaces. It is shown that monotone likelihood ratio (MLR) for the total score variable and nonlinear latent trait implies stochastic ordering (SO) of the total score variable, but may fail to imply SO of the nonlinear latent trait. The reason for this and conditions under which the implication holds are specified, based on a new, simpler proof of the fact that in the unidimensional case MLR implies SO. The approach is applied in knowledge space theory (KST), a combinatorial test theory. This leads to a (tentative) Mokken-type nonparametric axiomatization in the currently parametric theory of knowledge spaces. The nonparametric axiomatization is compared with the assumptions of the parametric basic local independence model which is fundamental in KST. It is concluded that this paper may provide a first step toward a basis for a possible fusion of the two split directions of psychological test theories IRT and KST.     

潜变量交互效应建模方法演变与简化

综述了近年来加入乘积指标的潜变量交互效应建模方法, 从产生乘积指标的策略、参数约束方法、均值结构与指标中心化的关系三个方面, 讨论了建模方法的简化进程。最后总结出同类方法中比较简洁又不失精确的潜变量交互效应建模方法—— 无需均值结构的无约束方法, 并给出了建模 步骤。     

Quality assurance in the clinical genetics setting—Report of a workshop

Participants in a panel discussion sponsored by thead hoc Quality Assurance Committee of the National Society of Genetic Counselors discuss early efforts to develop and implement quality assurance instruments at institutional, state, and regional levels. Uniform guidelines and self-assessment tools can help genetic counselors and clinical geneticists to provide the best possible care to individuals affected by genetic diseases. Further work will be needed to address aspects not covered here and to assure that guidelines allow for creative variation among professionals and centers. An interdisciplinary approach to such standard-setting is recommended.CGC     

Full Information Maximum Likelihood Estimation for Latent Variable Interactions With Incomplete Indicators

Researchers have developed missing data handling techniques for estimating interaction effects in multiple regression. Extending to latent variable interactions, we investigated full information maximum likelihood (FIML) estimation to handle incompletely observed indicators for product indicator (PI) and latent moderated structural equations (LMS) methods. Drawing on the analytic work on missing data handling techniques in multiple regression with interaction effects, we compared the performance of FIML for PI and LMS analytically. We performed a simulation study to compare FIML for PI and LMS. We recommend using FIML for LMS when the indicators are missing completely at random (MCAR) or missing at random (MAR) and when they are normally distributed. FIML for LMS produces unbiased parameter estimates with small variances, correct Type I error rates, and high statistical power of interaction effects. We illustrated the use of these methods by analyzing the interaction effect between advanced cancer patients’ depression and change of inner peace well-being on future hopelessness levels.