A unitary Neo-Piagetian/Neo-Eriksonian model of development: Fundamental assumptions and meta-issues

The article briefly reviews a stage model of change in human development that integrates a Neo-Piagetian model and a Neo-Eriksonian model into one unitary stage model across the lifespan (as presented in Young, 2011). The model suggests a generic model of stages in change. The article explores the fundamental assumptions underlying the model as well as considering meta-issues. The article adds to the book by describing the Neo-Eriksonian stages as reflections of a social “participatory” process. It adds to the change process in development by describing it as possibly reflecting “punctuated disequilibrium.” Finally, it adds a “multiple psychodynamics” model.     

Structure of RIASEC scores in China: A structural meta-analysis

A structural meta-analysis was conducted to evaluate the fit of four different representations of the relations among RIASEC types, [13] and [14] circular order model, Gati’s (1991) three-group partition model, Rounds and Tracey’s (1996) alternative three-group partition model, and Liu and Rounds’ (2003) modified octant model, on 29 RIASEC correlation matrices collected from Chinese participants. The randomization test of hypothesized order relations was used to evaluate model fit. The results indicated that Holland’s model had the worst fit and was lower than it is fit in US samples; while Gati’s and Rounds and Tracey’s models had best fit. The fit of the Liu and Rounds’ model lay between the fit of Holland’s model and the other models. There was minimal difference in this ordering of model fit across instrument, age, gender and region. These results are interpreted with respect to differences in Chinese culture relative to the US.     

How to use the diffusion model: Parameter recovery of three methods: EZ, fast-dm, and DMAT

Parameter recovery of three different implementations of the Ratcliff diffusion model was investigated: the EZ model (Wagenmakers, van der Maas, & Grasman, 2007), fast-dm (Voss & Voss, 2007), and DMAT (Vandekerckhove & Tuerlinckx, 2007). Their capacity to recover both the mean structure and individual differences in parameter values was explored. The three methods were applied to simulated data generated by the diffusion model, by the leaky, competing accumulator (LCA) model (Usher & McClelland, 2001) and by the linear ballistic accumulator (LBA) model (Brown & Heathcote, 2008). Results show that EZ and DMAT are better capable than fast-dm in recovering experimental effects on parameters. EZ was best in recovering individual differences in parameter values. When data were generated by the LCA model, the diffusion model estimates obtained with all three methods correlated well with corresponding LCA model parameters. No such one-on-one correspondence could be established between parameters of the LBA model and the diffusion model.     

The Generalized DINA Model Framework

The G-DINA (generalized deterministic inputs, noisy “and” gate) model is a generalization of the DINA model with more relaxed assumptions. In its saturated form, the G-DINA model is equivalent to other general models for cognitive diagnosis based on alternative link functions. When appropriate constraints are applied, several commonly used cognitive diagnosis models (CDMs) can be shown to be special cases of the general models. In addition to model formulation, the G-DINA model as a general CDM framework includes a component for item-by-item model estimation based on design and weight matrices, and a component for item-by-item model comparison based on the Wald test. The paper illustrates the estimation and application of the G-DINA model as a framework using real and simulated data. It concludes by discussing several potential implications of and relevant issues concerning the proposed framework.     

Testing a Bifactor Model of Relational and Physical Aggression in Early Childhood

Different approaches have been used to classify children as relationally aggressive, physically aggressive, or both relationally and physically aggressive (co-occurring aggression). The goal of the current study (N = 164, 50.9% boys, M _age = 47.75 months, SD = 7.37) was to test a bifactor model of aggression, which allows for aggression to be assessed dimensionally, and postulates a co-occurring aggression factor as well as unique relational and physical aggression factors, during early childhood. Aggression was measured using reliable observer and teacher reports of physical and relational aggression subscales. The two-factor model was an adequate fit to the data but the bifactor model was a significant improvement in model fit compared to the two-factor model. Alternative statistics for evaluating bifactor models were used in the current study. The measurement invariance (e.g., configural invariance, metric invariance, and scalar invariance) of the bifactor model was tested across gender and results from the bifactor model using teacher report showed that the model was invariant across gender. Lastly, the criterion validity of the model was examined by evaluating the relations between the bifactor model and observations of physical and relational aggression and results generally supported the validity of the bifactor model. Overall, results suggest that a bifactor model of aggression may be a useful method for studying aggression in early childhood.     

Kim On Reduction

In Mind in a Physical World (1998), Jaegwon Kim has recently extended his ongoing critique of `non-reductive materialist' positions in philosophy of mind by arguing that Nagel's model of reduction is the wrong paradigm in terms of which to contest the issue of psychophysical reduction, and that an altogether different model of scientific reduction – a functional model of reduction – is needed. In this paper I argue, first, that Kim's conception of the Nagelian model is substantially impoverished and potentially misleading; second, that his own functional model is problematic in several respects; and, third, that the basic idea underlying his functional model can well be accommodated within a properly reinterpreted Nagelian model. I conclude with some reflections on the issue of psychophysical reduction.     

不同条件下拟合指数的表现及临界值的选择

在本模拟研究中设计了6种样本容量,6种因子载荷,和4种评分等级,并考察了正态和非正态分布两种情况。采用的错误模型为参数误置（真模型中每个因子各由5个题目来测量,错误模型中则是第一个因子由6个题测量,另两个因子各由4个和5个题来测量,即有一个因子载荷被误置）模型。结果发现（1）样本量、载荷量、评分等级数和分布形态都对GOF的取值确有影响。其中分布形态的影响最大。NNFI、IFI在不同条件下的平均值是最稳定的,其次是CFI、RMSEA和SRMR。它们都算是值得推荐的GOF,尤其是NNFI和IFI。（2）在正态分布中,当样本量≥1000时,根据NNFI、IFI、CFI、RMSEA、SRMR对模型是否拟合做出判断时有很低的两类错误率,在样本量<1000时则不理想。在偏态条件下无论选择哪个GOF两类错误率都很高。（3）采用2指数策略在很多情况下也不能显著降低两类错误率。（4）由于在数据分布非正态,或正态但样本量<1000时是难判断模型是否拟合的。因此我们提出了2界值策略。即为每个GOF确定上下两个界值。低于下界值时可判断模型是不正确的,而高于上界值时则可判断模型是正确的。GOF取值处于上下界值之间时难以判断模型是否拟合,只能说越高拟合的可能性越大。这时就要通过跨样本验证和增加样本量来确定模型是否正确     

A Nested Comparison of Four Models of the Consequences of Role Perception Variables

Using a nested models approach, four models of the outcomes of role perception variables - the Bedeian and Armenakis (1981) model; the Schaubroeck, Cotton, and Jennings (1989) model; the Wunder, Dougherty, and Welsh (1982) model; and a proposed model - are compared. Results suggest that both fit indices and individual path significance tests are required to determine model parsimony.     

Loglinear Rasch model tests

Existing statistical tests for the fit of the Rasch model have been criticized, because they are only sensitive to specific violations of its assumptions. Contingency table methods using loglinear models have been used to test various psychometric models. In this paper, the assumptions of the Rasch model are discussed and the Rasch model is reformulated as a quasi-independence model. The model is a quasi-loglinear model for the incomplete subgroup × score × item 1 × item 2 × ... × itemk contingency table. Using ordinary contingency table methods the Rasch model can be tested generally or against less restrictive quasi-loglinear models to investigate specific violations of its assumptions.     

Nonlinear submodels of orthogonal linear models

A model containing linear and nonlinear parameters (e. g., a spatial multidimensional scaling model) is viewed as a linear model with free and constrained parameters. Since the rank deficiency of the design matrix for the linear model determines the number of side conditions needed to identify its parameters, the design matrix acts as a guide in identifying the parameters of the nonlinear model. Moreover, if the design matrix and the uniqueness conditions constitute anorthogonal linear model, then the associated error sum of squares may be expressed in a form which separates the free and constrained parameters. This immediately provides least squares estimates of the free parameters, while simplifying the least squares problem for those which are constrained. When the least squares estimates for a nonlinear model are obtained in this way,i.e. by conceptualizing it as a submodel, the final error sum of squares for the nonlinear model will be arestricted minimum whenever the side conditions of the model become real restrictions upon its submodel. In this case the design matrix for the embracing orthogonal model serves as a guide in introducing parameters into the nonlinear model as well as in identifying these parameters. The method of overwriting a nonlinear model with an orthogonal linear model is illustrated with two different spatial analyses of a three-way preference table.     

A maximum likelihood hierarchical disaggregate model for predicting choices of individuals

The absence of operational disaggregate lexicographic decision models and Tversky's observation that choice behavior is often inconsistent, hierarchical, and context dependent motivate the development of a maximum likelihood hierarchical (MLH) choice model. This new disaggregate choice model requires few assumptions and accommodates the three aspects of choice behavior noted by A. Tversky (1972, Journal of Mathematical Psychology, 9, 341–367). The model has its foundation in a prototype model developed by the authors. Unlike the deterministic prototype, however, MLH is a probabilistic model which generates maximum likelihood estimators of the aggregate “cutoff values.” The model is formulated as a concave programming problem whose solutions are therefore globally optimal. Finally, the model is applied to data from three separate studies where it is demonstrated to have superior performance over the prototype model in its predictive performance.     

Higher order training supporting competence,autonomy, relatedness (HOT-CAR): A model to improve learner drivers' higher order skills

Approaches to teaching young Learners to drive on-road often lack a strong, overarching theoretical framework. This paper proposes a transtheoretical model to guide instruction of higher-order skills – that are associated with reduced crash risk in young drivers – including established teaching techniques for effective instruction. Learnings from Self-Determination Theory (SDT) and the Goals for Driver Education framework (widely identified as best-practice but not effectively translated into practice) were integrated into the Higher Order Training supporting Competence, Autonomy, Relatedness (HOT-CAR) model. The model was empirically informed from naturalistic observation of professional in-vehicle lessons (n = 110) and a survey of young adolescent drivers (n = 1627). The HOT-CAR model is presented as a three-component framework that recognises learning to drive occurs within a broader system beyond the Learner and the instructor. The foundation of the model identifies the nature of the relationship between the Learner and the instructor that underlies the success of all other elements. The core of the model is the higher-order driving instruction approach including teaching strategies informed by SDT’s needs-supportive model. The context for the model incorporates some of the immediate considerations relevant to instruction; for example, the graduated driver licensing system, automated vehicle features, and peer influence. An example of the application of the model is provided to reflect the immediate practicality of the HOT-CAR model to driver training. This contributes to the limited road safety literature providing a practical solution to Learner driver training that has potential to reduce the crash risk of young novice drivers. Importantly, the model has potential to be applied and adapted to education and other training environments where higher-order skills are a safety–critical component.     

Models for ordinal hierarchical classes analysis

This paper proposes an ordinal generalization of the hierarchical classes model originally proposed by De Boeck and Rosenberg (1998). Any hierarchical classes model implies a decomposition of a two-way two-mode binary arrayM into two component matrices, called bundle matrices, which represent the association relation and the set-theoretical relations among the elements of both modes inM. Whereas the original model restricts the bundle matrices to be binary, the ordinal hierarchical classes model assumes that the bundles are ordinal variables with a prespecified number of values. This generalization results in a classification model with classes ordered along ordinal dimensions. The ordinal hierarchical classes model is shown to subsume Coombs and Kao's (1955) model for nonmetric factor analysis. An algorithm is described to fit the model to a given data set and is subsequently evaluated in an extensive simulation study. An application of the model to student housing data is discussed.     

Is speech alignment to talkers or tasks?

Speech alignment, or the tendency of individuals to subtly imitate each other’s speaking styles, is often assessed by comparing a subject’s baseline and shadowed utterances to a model’s utterances, often through perceptual ratings. These types of comparisons provide information about the occurrence of a change in subject’s speech, but they do not indicate that this change is toward the specific shadowed model. In three experiments, we investigated whether alignment is specific to a shadowed model. Experiment 1 involved the classic baseline-to-shadowed comparison, to confirm that subjects did, in fact, sound more like their model when they shadowed, relative to any preexisting similarities between a subject and a model. Experiment 2 tested whether subjects’ utterances sounded more similar to the model whom they had shadowed or to another, unshadowed model. In Experiment 3, we examined whether subjects’ utterances sounded more similar to the model whom they had shadowed or to another subject who had shadowed a different model. The results of all experiments revealed that subjects sounded more similar to the model whom they had shadowed. This suggests that shadowing-based speech alignment is not just a change, but a change in the direction of the shadowed model, specifically.     

EZ does it! Extensions of the EZ-diffusion model

In this rejoinder, we address two of Ratcliff’s main concerns with respect to the EZ-diffusion model (Ratcliff, 2008). First, we introduce “robust-EZ,” a mixture model approach to achieve robustness against the presence of response contaminants that might otherwise distort parameter estimates. Second, we discuss an extension of the EZ model that allows the estimation of starting point as an additional parameter. Together with recently developed, user-friendly software programs for fitting the full diffusion model (Vandekerckhove & Tuerlinckx, 2007; Voss & Voss, 2007), the development of the EZ model and its extensions is part of a larger effort to make diffusion model analyses accessible to a broader audience, an effort that is long overdue.     

现代测量理论下四大认知诊断模型述评

该文介绍并比较了现代测量理论下四大认知诊断模型的思想方法、模型结构及各自的特点性能等。LLTM是一个较早的认知诊断模型,它实现了认知与测量的结合;规则空间模型实现了对认知结构的诊断,并创造性地提出了Q矩阵理论;统一模型与融合模型是同一类模型：两者均沿用了规则空间模型的Q矩阵方法,但克服了规则空间模型中的一些不足;融合模型被认为是二十一世纪初创立的一个很成功的认知诊断模型。     

Developing TODAM: Three models for serial-order information

TODAM2, a theory of distributed associative memory, shows how item and associative information can be considered special cases of serial-order information. Consequently, it is important to get the right model for serial-order information. Here, we analyze and compare three distributed-memory models for serial-order information that use TODAM’s convolution-correlation formalism. These models are the chaining model, the chunking model, and a new model, the power-set model. The chaining model associates each item with its predecessor; the chunking model uses multiple convolutions andn-grams to form chunks; and the power-set model interassociates all items in a set in a particular way to form a chunk. The models are compared in terms of their performance on seven basic tests of serial-order information—namely, serial recall, backward recall, recall of missing items, sequential probe tests, positional probe tests, serial-to-paired-associate transfer, and item recognition. The strengths and weaknesses of each model are discussed.     

对归纳推理贝叶斯模型的检验

作者用实验比较检验特征归纳的贝叶斯模型、关联相似性模型、基于特征的归纳推理模型和相似性覆盖模型这四种模型。以大学生为被试的实验结果表明：1）在强关联强度一致时,被试的归纳推理基本符合贝叶斯模型和关联相似性模型的预测,在弱关联强度一致时,不符合这四种模型预测;2）在关联强度不一致时,关联强度效应不符合贝叶斯模型的预测;3）在关联强度一致时,贝叶斯模型和关联相似性模型的预测结果是一致的,不能区分两个模型。实验结果较多地支持贝叶斯模型和关联相似性模型。     

Search for multiple targets: Evidence for memory-based control of attention

There are two opposing models with regard to the function of memory in visual search: a memorydriven model and a memory-free model. Recently, Horowitz and Wolfe (2001) investigated a multipletarget search task. Participants were required to decide whether or not there were at leastn targets present. They demonstrated that the reaction time ×n function has a positive and accelerated curve. They argued that the memory-free model predicts this curve, whereas the memory-driven model predicts a linear function. In this study, I varied the total set sizes of a multiple-target search task and fitted the models separately for eachn condition. The model fit indicated that the memory-driven model is more appropriate than the memory-free model in eachn condition. These results suggest that an amnesic process does not cause the positive accelerated curve of the reaction time ×n function but that it is the result of the time needed to examine each additionaln item.     

阅读范文对小学生作文成绩的影响

为考察阅读范文是否能够提高三年级小学生记叙文写作的成绩,在建立低年级小学生记叙文写作评价指标的基础上,选择1篇完整范文并设计8篇不同类型的不完整范文,选取300名三年级小学生为被试进行了实验研究。实验结果表明:(1)阅读完整范文和联结内容式、补充中间式、补充开头式、补充结尾式等不完整范文能够明显提高小学生记叙文写作结构分项的成绩,阅读其他4种类型的不完整范文作用不明显。(2)阅读完整的和8种不完整范文均能明显提高小学生在记叙文写作内容分项的成绩。(3)除了补充开头式、补充中间和结尾式两种不完整范文之外,阅读其他7种范文均能明显提高作文词句分项的成绩。(4)阅读范文对避免写作中出现错别字、错用标点符号和病句无显著作用。