A multitrait-multimethod model with minimal assumptions

A new model of confirmatory factor analysis (CFA) for multitrait-multimethod (MTMM) data sets is presented. It is shown that this model can be defined by only three assumptions in the framework of classical psychometric test theory (CTT). All other properties of the model, particularly the uncorrelated-ness of the trait with the method factors are logical consequences of the definition of the model. In the model proposed there are as many trait factors as different traits considered, but the number of method factors is one fewer than the number of methods included in an MTMM study. The covariance structure implied by this model is derived, and it is shown that this model is identified even under conditions under which other CFA-MTMM models are not. The model is illustrated by two empirical applications. Furthermore, its advantages and limitations are discussed with respect to previously developed CFA models for MTMM data.     

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.     

TEACHING AUTISTIC CHILDREN CONVERSATIONAL SPEECH USING VIDEO MODELING

We assessed the effects of video modeling on acquisition and generalization of conversational skills among autistic children. Three autistic boys observed videotaped conversations consisting of two people discussing specific toys. When criterion for learning was met, generalization of conversational skills was assessed with untrained topics of conversation; new stimuli (toys); unfamiliar persons, siblings, and autistic peers; and other settings. The results indicated that the children learned through video modeling, generalized their conversational skills, and maintained conversational speech over a 15-month period. Video modeling shows much promise as a rapid and effective procedure for teaching complex verbal skills such as conversational speech.     

Bayesian parameter estimation in the Expectancy Valence model of the Iowa gambling task

The purpose of the popular Iowa gambling task is to study decision making deficits in clinical populations by mimicking real-life decision making in an experimental context. Busemeyer and Stout [Busemeyer, J. R., & Stout, J. C. (2002). A contribution of cognitive decision models to clinical assessment: Decomposing performance on the Bechara gambling task. Psychological Assessment, 14, 253-262] proposed an “Expectancy Valence” reinforcement learning model that estimates three latent components which are assumed to jointly determine choice behavior in the Iowa gambling task: weighing of wins versus losses, memory for past payoffs, and response consistency. In this article we explore the statistical properties of the Expectancy Valence model. We first demonstrate the difficulty of applying the model on the level of a single participant, we then propose and implement a Bayesian hierarchical estimation procedure to coherently combine information from different participants, and we finally apply the Bayesian estimation procedure to data from an experiment designed to provide a test of specific influence.     

A longitudinal study of student-teacher relationship quality, difficult temperament, and risky behavior from childhood to early adolescence

This study examines the mediating role of student-teacher relationship quality (conflict and closeness) in grades 4, 5, and 6 on the relation between background characteristics, difficult temperament at age 4½ and risky behavior in 6th grade. The longitudinal sample of participants (N = 1156) was from the NICHD Study of Early Child Care and Youth Development. Structural equation modeling was used to estimate paths from (a) background characteristics to student-teacher relationship quality and risky behavior, (b) temperament to student-teacher relationship quality and risky behavior, and (c) student-teacher relationship quality to risky behavior. Findings indicate that students' family income, gender, receipt of special services, and more difficult temperament were associated with risky behavior. In addition, student-teacher conflict was a mediator. Students with more difficult temperaments were more likely to report risky behavior and to have conflict in their relationships with teachers. More conflict predicted more risky behavior. Closer student-teacher relationships were associated with less risky behavior. Results suggest negative relationships, specifically student-teacher relationships, may increase the risk that certain adolescents will engage in risky behavior.     

Examining classroom influences on student perceptions of school climate: The role of classroom management and exclusionary discipline strategies

There is growing emphasis on the use of positive behavior supports rather than exclusionary discipline strategies to promote a positive classroom environment. Yet, there has been limited research examining the association between these two different approaches to classroom management and students' perceptions of school climate. Data from 1902 students within 93 classrooms that were nested within 37 elementary schools were examined using multilevel structural equation modeling procedures to investigate the association between two different classroom management strategies (i.e., exclusionary discipline strategies and the use of positive behavior supports) and student ratings of school climate (i.e., fairness, order and discipline, student–teacher relationship, and academic motivation). The analyses indicated that greater use of exclusionary discipline strategies was associated with lower order and discipline scores, whereas greater use of classroom-based positive behavior supports was associated with higher scores on order and discipline, fairness, and student–teacher relationship. These findings suggest that pre-service training and professional development activities should promote teachers' use of positive behavior support strategies and encourage reduced reliance on exclusionary discipline strategies in order to enhance the school climate and conditions for learning.     

Analysis of the factor structure of the Sociocultural Attitudes Towards Appearance Questionnaire (SATAQ-3) in Spanish secondary-school students through exploratory structural equation modeling

The aims of the present study were: (1) to assess the factor structure of the SATAQ-3 in Spanish secondary-school students by means of exploratory factor analysis (EFA), confirmatory factor analysis (CFA) and exploratory structural equation modeling (ESEM) models; and (2) to study its invariance by sex and school grade. ESEM is a technique that has been proposed for the analysis of internal structure that overcomes some of the limitations of EFA and CFA. Participants were 1559 boys and girls in grades seventh to tenth. The results support the four-factor solution of the original version, and reveal that the best fit was obtained with ESEM, excluding Item 20 and with correlated uniqueness between reverse-keyed items. Our version shows invariance by sex and grade. The differences between scores of different groups are in the expected direction, and support the validity of the questionnaire. We recommend a version excluding Item 20 and without reverse-keyed items.     

Two routes to face perception: evidence from psychophysics and computational modeling

The aim of this study was to separately analyze the role of featural and configural face representations. Stimuli containing only featural information were created by cutting the faces into their parts and scrambling them. Stimuli only containing configural information were created by blurring the faces. Employing an old-new recognition task, the aim of Experiments 1 and 2 was to investigate whether unfamiliar faces (Exp. 1) or familiar faces (Exp. 2) can be recognized if only featural or configural information is provided. Both scrambled and blurred faces could be recognized above chance level. A further aim of Experiments 1 and 2 was to investigate whether our method of creating configural and featural stimuli is valid. Pre-activation of one form of representation did not facilitate recognition of the other, neither for unfamiliar faces (Exp. 1) nor for familiar faces (Exp. 2). This indicates a high internal validity of our method for creating configural and featural face stimuli. Experiment 3 examined whether features placed in their correct categorical relational position but with distorted metrical distances facilitated recognition of unfamiliar faces. These faces were recognized no better than the scrambled faces in Experiment 1, providing further evidence that facial features are stored independently of configural information. From these results we conclude that both featural and configural information are important to recognize a face and argue for a dual-mode hypothesis of face processing. Using the psychophysical results as motivation, we propose a computational framework that implements featural and configural processing routes using an appearance-based representation based on local features and their spatial relations. In three computational experiments (Experiments 4–6) using the same sets of stimuli, we show how this framework is able to model the psychophysical data.     

记叙文阅读中时间心理表征的建构：动态观还是静态观

探讨读者在文本阅读中如何通过一系列展开事件的描述建构心理表征。实验一探讨在中间事件持续时间长／短条件下对首尾呼应句阅读时间和对探测词反应时间的影响;结果表明,读者对第一事件信息的获得受中间事件的持续时间长短的影响。实验二探讨当信息储存在长时工作记忆中时能否得出与实验一相一致的结果。结果发现,读者对第一事件信息的获得不受中间事件的持续时间长短的影响。实验三考察当用明确的时间副词来表明持续时间的长短时,连续性的事件是否还存在着时间距离效应。实验结果与实验二的相一致。整个研究结果表明,时间心理表征的建构是动态观还是静态观,主要取决于是否存在时间距离效应。