智力落后的成因--当代智力理论新解

智力落后的成因历来存在争论。本文在当代复杂系统智力理论的视野之下．从Sternberg的三元智力理论和Das的PASS模型入手,分析了智力落后本质及成因的新解．揭示了智力落后理论研究的认知心理学新走向。     

The First-Order Theories of Dedekind Algebras

A Dedekind Algebra is an ordered pair (B,h) where B is a non-empty set and h is an injective unary function on B. Each Dedekind algebra can be decomposed into a family of disjoint, countable subalgebras called configurations of the Dedekind algebra. There are N₀ isomorphism types of configurations. Each Dedekind algebra is associated with a cardinal-valued function on omega called its configuration signature. The configuration signature of a Dedekind algebra counts the number of configurations in the decomposition of the algebra in each isomorphism type.The configuration signature of a Dedekind algebra encodes the structure of that algebra in the sense that two Dedekind algebras are isomorphic iff their configuration signatures are identical. Configuration signatures are used to establish various results in the first-order model theory of Dedekind algebras. These include categoricity results for the first-order theories of Dedekind algebras and existence and uniqueness results for homogeneous, universal and saturated Dedekind algebras. Fundamental to these results is a condition on configuration signatures that is necessary and sufficient for elementary equivalence.     

Model comparison of nonlinear structural equation models with fixed covariates

Recently, it has been recognized that the commonly used linear structural equation model is inadequate to deal with some complicated substantive theory. A new nonlinear structural equation model with fixed covariates is proposed in this article. A procedure, which utilizes the powerful path sampling for computing the Bayes factor, is developed for model comparison. In the implementation, the required random observations are simulated via a hybrid algorithm that combines the Gibbs sampler and the Metropolis-Hastings algorithm. It is shown that the proposed procedure is efficient and flexible; and it produces Bayesian estimates of the parameters, latent variables, and their highest posterior density intervals as by-products. Empirical performances of the proposed procedure such as sensitivity to prior inputs are illustrated by a simulation study and a real example.This research is fully supported by a grant from the Research Grant Council of the Hong Kong Special Administrative Region, China (Project No. CUHK 4346/01H). The authors are thankful to the Editor, the Associate Editor, and anonymous reviewers for valuable comments which improve the paper significantly, and grateful to ICPSR and the relevant funding agency for allowing use of the data in the example. The assistance of Michael K.H. Leung and Esther L.S. Tam is gratefully acknowledged.     

Rural Neighborhoods and Child Aggression

Structural equation modeling with latent variables was used to evaluate the direct and mediated effects of a neighborhood risk factor (negative teen behaviors) on the parent-report aggressive behavior of 213 students in grades 3 through 5 attending a school in a low-income, rural community. Contagion and social control hypotheses were examined as well as hypotheses about whether the neighborhood served as a microsystem or exosystem for rural pre-adolescents. Analyses took into account the clustering of students and ordinal nature of the data. Findings suggest that rural neighborhoods may operate as both a microsystem and exosystem for children, with direct contagion effects on their aggressive behaviors as well as indirect social control effects through parenting practices. Direct effects on aggression were also found for parenting practices and child reports of friends’ negative behaviors. Pre-adolescence may be a transitional stage, when influences of the neighborhood on child behavior begin to compete with influences of caregivers. Findings can inform the timing and targets of violence prevention in rural communities.     

Path analytic examination of a cognitive model of PTSD

Ehlers and Clark (2000) developed a cognitive model of posttraumatic stress disorder (PTSD) symptom maintenance which implicated the role of posttraumatic cognitions and aspects of the trauma memory in maintaining symptoms via an increased sense of current threat. The aim of the current study was to empirically test a variant of this model using path analysis. Participants in the current study were 514 undergraduates at a midwestern university who reported experiencing at least one traumatic event. Path analyses examined various models of the possible relationships between one’s posttraumatic cognitions and the centrality of the traumatic event to the sense of self (considered an aspect of memory integration) in predicting current level of PTSD symptoms. Results indicate that both event centrality and posttraumatic cognitions are unique and independent predictors of current symptom level. Overall, the results of this study support aspects of Ehlers and Clark’s cognitive model of PTSD; cognitive appraisals of the self and centrality of the event were highly related to levels of distress. However, the current study suggests that overly integrated trauma memories may lead to greater distress and not poorly integrated ones as suggested by Ehlers and Clark.     

决策任务反应模式对偏好反转的影响

在经典彩票问题研究的基础上,探讨了匹配和选择两种反应模式及其先后顺序对被试偏好反转的影响,以及被试性别与其偏好反转的关系。研究结果发现:(1)反应模式的变化导致偏好反转的发生;(2)偏好反转存在反应顺序效应,先匹配后选择条件下的偏好反转率显著大于先选择后匹配条件下的偏好反转率;研究结果不支持后悔理论;(3)不同性别被试在选择和匹配任务中的偏好及其反转率没有显著性差异。     

Computational behavior dynamics: an alternative description of Nevin (1969).

A computational processing behavior-dynamic model was instantiated in the form of a computer program that "behaved" on the task developed by Nevin (1969). In this classic discrete-trials experiment, the relative frequency of choosing a response alternative matched the relative frequency of reinforcement for that alternative, the local structure of responding was opposite that predicted by momentary maximizing (i.e., the probability of a changeover decreased with run length), and absolute and relative response rates varied independently. The behavior-dynamic model developed here qualitatively reproduced these three results (but not in quantitative and specific detail) and also generated some interesting, as-yet-untested predictions about performance in Nevin's task. The model was discussed as an example of a stochastic behavior-dynamic alternative to algebraic behavior theory.     

汉字记忆中错误联接的码相加效应

采用错误联接的实验范式考察汉字记忆中的码相加效应。实验1采用形码加义码,结果发现对义似形似组的特征诱字错误再认率显著高于义异形似组的。实验2采用形码加音码．结果发现对音似形似组的诱字的错误再认率显著高于音异形似组的。研究表明汉语记忆中的错误联接存在码相加效应。研究结果可用激活混淆来源理论解释。     

Global Model Analysis of Cognitive Variability

Residual fluctuations produced in typical experimental methodologies are examined as correlated noises. The effective range of the correlations was assessed by determining whether the decay over look-back time is better described as a power law or exponential. Both of these decay laws contain free parameters and it is argued that it is not possible to distinguish their models on the basis of simple measures of goodness-of-fit. Global analyses that evaluate models on the basis of how well they generalize are conducted. The models are examined in terms of three constructs that all bear on generalization: cross-validity, flexibility, and representativeness. Quantitative assessment of a large ensemble of data suggests that the correlations decay over time as a power law. The conclusion is that human residual fluctuation is a correlated fractal.     

Estimation of the Nonlinear Random Coefficient Model when Some Random Effects Are Separable

A method is presented for marginal maximum likelihood estimation of the nonlinear random coefficient model when the response function has some linear parameters. This is done by writing the marginal distribution of the repeated measures as a conditional distribution of the response given the nonlinear random effects. The resulting distribution then requires an integral equation that is of dimension equal to the number of nonlinear terms. For nonlinear functions that have linear coefficients, the improvement in computational speed and accuracy using the new algorithm can be dramatic. An illustration of the method with repeated measures data from a learning experiment is presented.