A structural equation modeling of executive functions,IQ and mathematical skills in primary students: Differential effects on number production,mental calculus and arithmetical problems

Though the relationship between executive functions (EFs) and mathematical skills has been well documented, little is known about how both EFs and IQ differentially support diverse math domains in primary students. Inconsistency of results may be due to the statistical techniques employed, specifically, if the analysis is conducted with observed variables, i.e., regression analysis, or at the latent level, i.e., structural equation modeling (SEM). The current study explores the contribution of both EFs and IQ in mathematics through an SEM approach. A total of 118 8- to 12-year-olds were administered measures of EFs, crystallized (Gc) and fluid (Gf) intelligence, and math abilities (i.e., number production, mental calculus and arithmetical problem-solving). Confirmatory factor analysis (CFA) offered support for the three-factor solution of EFs: (1) working memory (WM), (2) shifting, and (3) inhibition. Regarding the relationship among EFs, IQ and math abilities, the results of the SEM analysis showed that (i) WM and age predict number production and mental calculus, and (ii) shifting and sex predict arithmetical problem-solving. In all of the SEM models, EFs partially or totally mediated the relationship between IQ, age and math achievement. These results suggest that EFs differentially supports math abilities in primary-school children and is a more significant predictor of math achievement than IQ level.     

Processing speed, intelligence, creativity, and school performance: Testing of causal hypotheses using structural equation models

According to mental speed theory of intelligence, the speed of information processing constitutes an important basis for cognitive abilities. However, the question, how mental speed relates to real world criteria, like school, academic, or job performance, is still unanswered. The aim of the study is to test an indirect speed-factor model in comparison to rivaling models explaining the relationships between different mental abilities and performance. In this speed-factor model, basic cognitive processing is assumed to influence higher mental abilities (IQ and creativity). Intelligence and creativity themselves should be valid predictors of school performance. We computed bivariate correlations and structural equation models to test this hypothesis, using indicators of processing speed [Zahlen-Verbindungs-Test (ZVT) and Coding Test], psychometric intelligence [Kognitiver Fähigkeits-Test (KFT) and Raven's Advanced Progressive Matrices (APM)], creativity [Verbaler Kreativitäts-Test (VKT) and Verwendungs-Test (VWT)] and school performance (grades). In a sample of 271 students from German gymnasiums (Class Levels 9 to 11) the speed-factor model can reproduce at best the empirical relationships between processing speed, intelligence, creativity, and school performance: It assumes that processing speed influences higher mental abilities (intelligence and creativity), which, in the sequel, influence school performance. Therefore, processing speed seems to have no direct effect on school performance; the effect is indirect as it operates via mediation through higher cognitive abilities.     

归类的相似性对比模型研究综述

本文阐述了近期归类中的相似性对比模型的研究,首先介绍了相似性对比的空间模型、基于特征的对比模型以及最近提出的结构匹配模型,并且详细阐述结构匹配模型观点以及它的应用方面的研究,旨在抛砖引玉,引起更多的人们来关注本领域的研究与发展。     

Neural network applications in consumer behavior

This article introduces the concepts and terminology of artificial neural networks. The approach is demonstrated on data that represent a domain of interest to the consumer psychologist. ANNs are mathematical models that are commonly used in business applications to model relationships between variables. A key strength of ANNs is their flexibility, i.e. their ability to easily accommodate linear and non-linear relationships without any a priori functional form specification. They can easily be used to study topics of interest to consumer psychologists such as persuasion, influence, segmentation etc and can offer distinct advantages over traditional statistical techniques such as ANOVA and regression. We demonstrate the application of ANNs in three different areas: regression, non-linear principal component analysis and classification.     

Impulsivity and reward sensitivity within the pen model: A test of discriminant hypotheses

Impulsivity and reward sensitivity are often treated as interchangeable constructs. This conflation may be traced back to Gray’s interpretation of impulsivity as the trait level manifestation of the Behavioral Activation System (BAS), that mediates sensitivity to rewards. In this study (N = 696) we evaluated discriminant hypotheses regarding the relationships between BAS-mediated reward sensitivity, impulsivity and Eysenck’s PEN superfactors. We hypothesized that reward sensitivity would be mainly linked with Extraversion, and that impulsivity would be primarily connected with Psychoticism. Hypotheses were tested using structural equation modelling and equality constraints tests. Results mostly supported our expectations: reward sensitivity was more strongly related to Extraversion than to the other PEN superfactors, while impulsivity was more strongly related to Psychoticism and Neuroticism. Implications for BAS and impulsivity research are discussed.     

Clock drawing performance and brain morphology in mild cognitive impairment and Alzheimer's disease

The Clock Drawing Test (CDT) is a widely used instrument in the neuropsychological assessment of Alzheimer's disease (AD). As CDT performance necessitates several cognitive functions (e.g., visuospatial and constructional abilities, executive functioning), an interaction of multiple brain regions is likely. Fifty-one subjects with mild cognitive impairment, 23 with AD and 15 healthy controls underwent high-resolution magnetic resonance imaging. Optimized voxel-based morphometry (VBM) was performed to investigate the putative association between CDT performance and gray matter (GM) density throughout the entire brain. In the first step of analysis (p<.001, uncorrected), VBM revealed a reduced GM density in numerous cortical (temporal lobe, frontal lobe, parietal lobe, cerebellum) and subcortical (thalamus, basal ganglia) brain regions to be associated with poorer CDT performance. When corrected for multiple comparisons (p<.01), the associations remained significant predominantly in the left temporal and--less pronounced--the right temporal lobe. VBM demonstrated CDT performance to depend on the integrity of widely distributed cortical and subcortical areas in both brain hemispheres with accentuation in the left-sided temporal lobe region.     

Modeling and prediction of driver preparations for making a right turn based on vehicle velocity and traffic conditions while approaching an intersection

This paper focuses on modeling and predicting the influence of a vehicle’s velocity and the relative position between a driver’s vehicle and a vehicle to the front or rear on the onset of driver preparations for making a right turn at an intersection. Repeated experiments were carried out on a public road to measure driver preparations, including releasing the accelerator pedal, moving the right foot to cover the brake pedal, and activating the turn signal, as well as to record vehicle velocity and the relative distances to the leading and following vehicles. Structural equation modeling was applied to estimate these relationships quantitatively. Two separate latent variables accounting for the interaction between the driver’s vehicle and leading or following vehicles, and the onset point where driving behavior changes from straight mode to preparation mode before a right turn, were introduced in the specification of the structural equation model. The model estimates and testing indicate that the proposed structural equation model represents well the relationship hypothesized by observational analysis: that the vehicle velocity and the traffic conditions surrounding the driver’s vehicle strongly influence the driver’s deceleration and more weakly influenced turn signal activation. The proposed structural equation model contributes to the prediction of the onset locations of covering the brake pedal and activating the turn signal based on the vehicle velocity and the relative distances to the front and rear vehicles when the accelerator pedal is released. The prediction accuracy is high compared with predictions in which the vehicle velocity and the headway or rear distances are not taken into account or predictions using a single regression model with one independent variable, namely driving speed. Finally, a possible new addition to in-vehicle navigation systems that detects unusual driver behavior by predicting the driver’s preparatory maneuvers is discussed.     

Antecedents of mentoring support: a meta-analysis of individual,relational, and structural or organizational factors

The value of mentoring is growing substantially as organizations take a renewed interest in employee development to better survive in the dynamic and competitive market today. In the wake of this renewed interest, this meta-analysis was conducted to quantitatively review the multi-level antecedents (e.g., individual, relational, and structural/organizational) of different kinds of mentoring support (e.g., career, psychosocial, role modeling) in organizational settings and to revisit the theoretical underpinnings of each antecedent. Results indicated some key antecedents of mentoring support at individual (e.g., protégé's proactivity, protégé's learning goal orientation, mentor's transformational leadership), relational (e.g., affect based trust, perceived similarity), and structural/organizational levels (e.g., organizational support for mentoring, supervisory mentoring). Recommendations for future research and organizational practice of mentoring are presented.     

A causal model theory of the meaning of cause, enable, and prevent

The verbs cause , enable , and prevent express beliefs about the way the world works. We offer a theory of their meaning in terms of the structure of those beliefs expressed using qualitative properties of causal models, a graphical framework for representing causal structure. We propose that these verbs refer to a causal model relevant to a discourse and that "A causes B" expresses the belief that the causal model includes a link from A to B. "A enables/allows B" entails that the model includes a link from A to B, that A represents a category of events necessary for B, and that an alternative cause of B exists. "A prevents B" entails that the model includes a link from A to B and that A reduces the likelihood of B. This theory is able to account for the results of four experiments as well as a variety of existing data on human reasoning.     

Structural equations and causation: six counterexamples

Hall [(2007), Philosophical Studies, 132, 109–136] offers a critique of structural equations accounts of actual causation, and then offers a new theory of his own. In this paper, I respond to Hall’s critique, and present some counterexamples to his new theory. These counterexamples are then diagnosed.