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.     

Specificity of cognitive and behavioral variables to Positive and Negative Affect

The Tripartite Model proposes that a combination of greater Negative Affect (NA) and reduced Positive Affect (PA) contributes to depressive symptoms. The purpose of this study was to test a model of affective experience in which cognitive variables (i.e., negative cognitions and appraisals) are uniquely related to NA but not PA, and in which behavioral variables (i.e., activity participation) are uniquely associated with PA but not NA. Participants included 88 spousal Alzheimer caregivers (mean age = 74 years). Multiple regression models, in which negative cognitions (i.e., helplessness, blames self, and negative appraisals) and activity participation (i.e., frequency of engaging in social and recreational activities) were used to predict depressive symptoms, PA and NA. Results indicated that while helplessness, blaming oneself, negative appraisals, and activity participation all significantly predicted depressive symptoms, only negative cognitive variables significantly predicted NA, and only activity participation significantly predicted PA. These data confirm that depressive experience consists of two relatively independent components - increased Negative Affect and reduced Positive Affect - which have unique correlates in negative cognitions and activity participation. If confirmed, the findings suggest the utility of focusing interventions on each of these components in the management of depressive symptoms.     

Is Psychology Based on a Methodological Error?

It is believed a proven fact that variables in social and personality psychology match to normal distribution with its single peak. Multiple peaks are explained by independent variables. However, after a comprehensive data analysis of more than 8.000 patients and on the basis of a bio-psycho-social model with 27 scales, we arrived at the conclusion that normal distribution and the psychometric error theory cannot withstand critical analysis in large samples. Beyond the “truth” that is proved by distribution-dependent statistical inferences, there exists another “truth” that is denied by the empirical doctrine. This “truth” is influenced by compensatory belief systems and explains paradoxes in quality of life research. We hypothesize that items, referred to life risks are micro-stressors, triggering self-regulatory processes as a humanly inherent response, deeply anchored in human evolution. Especially when exposed to threatening experiences, self-focused attention generates amplified multimodal distributions and subverts the methodological premises by an ambivalence-bias between thrill and threat, hopes and fears, pleasure and pain, success and failure, etc. In this article we want to focus attention to the incommensurability between test theoretical axioms and the way people usually respond to self-focused items. We discuss basic distribution patterns and approach to an evolutionary theory of fluctuation of validity.

Separability of item and person parameters in response time models

This paper discusses two forms of separability of item and person parameters in the context of response time (RT) models. The first is separate sufficiency: the existence of sufficient statistics for the item (person) parameters that do not depend on the person (item) parameters. The second is ranking independence: the likelihood of the item (person) ranking with respect to RTs does not depend on the person (item) parameters. For each form a theorem stating sufficient conditions, is proved. The two forms of separability are shown to include several (special cases of) models from psychometric and biometric literature. Ranking independence imposes no restrictions on the general distribution form, but on its parametrization. An estimation procedure based upon ranks and pseudolikelihood theory is discussed, as well as the relation of ranking independence to the concept of double monotonicity.I am indebted to Wim van der Linden for bringing Thissen's (1983) paper to my notice, and to Martijn Berger, Frans Tan, and the anonymous reviewers for their constructive comments on earlier drafts of this paper.     

分时距认知特点的研究

本研究探讨了分时距估计的认知特点,检验了SS模型、PT模型和CS模型的预测效度,结果表明：分时距估计主要是在信息提取阶段采用分段推算策略对时间信息进行重建的过程,变化／分割和注意分配对分时距估计有显著影响;SS模型的预测效度最低,PT、CS模型的预测效度较高。     

拓展后的GGUM在LOT-R中的适用性分析

该研究对拓广等级展开模型（GGUM）进行了拓展,取消GGUM中关于主观反应类别阈限对称的假设,并将拓展之后的新模型和GGUM同时用于生活取向测验修订版（LOT-R）的被试反应数据分析,采用新编的单项目、两项目对和三项目组χ2/df计算程序计算和比较新模型和GGUM在该测验数据上的拟合差异。结果显示,新编程序与Stark等人开发的MODFIT程序具有同样的有效性,新模型在这些指标上的值显著小于GGUM,并且均小于3,表明新模型较GGUM更适合于分析LOT-R的反应数据,说明新模型更适用于分析具有多个评定等级的人格测验数据。根据以上结果,该研究认为,未来人格测验的数据分析应该使用没有对主观反应类别阈限进行对称限定的新拓展的模型更合理。     

Computational exploration of metaphor comprehension processes using a semantic space model

Recent metaphor research has revealed that metaphor comprehension involves both categorization and comparison processes. This finding has triggered the following central question: Which property determines the choice between these two processes for metaphor comprehension? Three competing views have been proposed to answer this question: the conventionality view ( Bowdle & Gentner, 2005 ), aptness view ( Glucksberg & Haught, 2006b ), and interpretive diversity view ( Utsumi, 2007 ); these views, respectively, argue that vehicle conventionality, metaphor aptness, and interpretive diversity determine the choice between the categorization and comparison processes. This article attempts to answer the question regarding which views are plausible by using cognitive modeling and computer simulation based on a semantic space model. In the simulation experiment, categorization and comparison processes are modeled in a semantic space constructed by latent semantic analysis. These two models receive word vectors for the constituent words of a metaphor and compute a vector for the metaphorical meaning. The resulting vectors can be evaluated according to the degree to which they mimic the human interpretation of the same metaphor; the maximum likelihood estimation determines which of the two models better explains the human interpretation. The result of the model selection is then predicted by three metaphor properties (i.e., vehicle conventionality, aptness, and interpretive diversity) to test the three views. The simulation experiment for Japanese metaphors demonstrates that both interpretive diversity and vehicle conventionality affect the choice between the two processes. On the other hand, it is found that metaphor aptness does not affect this choice. This result can be treated as computational evidence supporting the interpretive diversity and conventionality views.