Nascent body ego: Metapsychological and neurophysiological aspects

For Freud, body ego was the organizing basis of the structural theory. He defi ned it as a psychic projection of the body surface. Isakower's and Lewin's classical fi ndings suggest that the body surface experiences of nursing provide the infant with sensory-affective stimulation that initiates a projection of sensory processes towards the psychic realm. During nursing, somato-sensory, gustatory and olfactory modalities merge with a primitive somatic affect of satiation, whereas auditory modality is involved more indirectly and visual contact more gradually. Repeated regularly, such nascent experiences are likely to play a part in the organization of the primitive protosymbolic mental experience. In support of this hypothesis, the authors review fi ndings from a neurophysiological study of infants before, during and after nursing. Nursing is associated with a signifi cant amplitude change in the newborn electroencephalogram (EEG), which wanes before the age of 3 months, and is transformed at the age of 6 months into rhythmic 3-5 Hz hedonic θ-activity. Sucking requires active physiological work, which is shown in a regular rise in heart rate. The hypothesis of a sensory-affective organization of the nascent body ego, enhanced by nursing and active sucking, seems concordant with neurophysiological phenomena related to nursing.     

The effect of product type on value linkages in the means‐end chain: implications for theory and method

Means‐end chain (MEC) theory proposes that consumer motivation can only be understood in terms of the hierarchical linkages between attributes, consequences and values. Other researchers have suggested a much more immediate impact of values on motivation. Seeking to explain these conflicting views, this research suggests and empirically tests the proposition that the role of values in consumer motivation differs by product type and also tests that the linkages are not affected by individual differences in the need for cognition. A sample of 191 consumers indicated their motivation to consume utilitarian and non‐utilitarian products using an adapted association pattern matrix technique. Responses were analysed using mixed‐design ANOVAs with planned comparisons. Results indicate significant differences related to product type in the role of values in consumer motivation. Limitations, implications for MEC theory and future research are discussed. Copyright © 2004 Henry Stewart Publications Ltd.     

认知诊断模型中项目水平模型比较统计量的健壮性

使用模拟研究方法比较了以往研究中提出的基于观察信息矩阵、三明治矩阵的Wald（分别表示为W_Obs、W_Sw）、似然比（Likelihood Ratio）统计量以及新提出的基于经验交叉相乘信息矩阵的Wald统计量（W_XPD）在模型——数据失拟条件下进行项目水平上模型比较时的表现。结果显示：（1）W_Sw的一类错误控制率有很强的健壮性。（2）W_XPD在Q矩阵错误设定的大多数条件下的表现优于W_Sw。结论：模型—数据拟合良好时可以使用W_Sw进行项目水平上的模型比较,当模型与数据失拟时W_XPD可能是更好的选择。     

Graph-theoretic representations for proximity matrices through strongly-anti-Robinson or circular strongly-anti-Robinson matrices

There are various optimization strategies for approximating, through the minimization of a least-squares loss function, a given symmetric proximity matrix by a sum of matrices each subject to some collection of order constraints on its entries. We extend these approaches to include components in the approximating sum that satisfy what are called the strongly-anti-Robinson (SAR) or circular strongly-anti-Robinson (CSAR) restrictions. A matrix that is SAR or CSAR is representable by a particular graph-theoretic structure, where each matrix entry is reproducible from certain minimum path lengths in the graph. One published proximity matrix is used extensively to illustrate the types of approximation that ensue when the SAR or CSAR constraints are imposed.The authors are indebted to Boris Mirkin who first noted in a personal communication to one of us (LH, April 22, 1996) that the optimization method for fitting anti-Robinson matrices in Hubert and Arabie (1994) should be extendable to the fitting of strongly anti-Robinson matrices as well.     

The mixed model for multivariate repeated measures: validity conditions and an approximate test

Repeated measures on multivariate responses can be analyzed according to either of two models: a doubly multivariate model (DMM) or a multivariate mixed model (MMM). This paper reviews both models and gives three new results concerning the MMM. The first result is, primarily, of theoretical interest; the second and third have implications for practice. First, it is shown that, given multivariate normality, a condition called multivariate sphericity of the covariance matrix is both necessary and sufficient for the validity of the MMM analysis. To test for departure from multivariate sphericity, the likelihood ratio test can be employed. The second result is an approximation to the null distribution of the likelihood ratio test statistic, useful for moderate sample sizes. Third, for situations satisfying multivariate normality, but not multivariate sphericity, a multivariate correction factor is derived. The correction factor generalizes Box's and can be used to construct an adjusted MMM test.I am grateful to an anonymous referee for carefully attending to the mathematical details of this paper.     

Approximating a symmetric matrix

We examine the least squares approximationC to a symmetric matrixB, when all diagonal elements get weightw relative to all nondiagonal elements. WhenB has positivityp andC is constrained to be positive semi-definite, our main result states that, whenw1/2, then the rank ofC is never greater thanp, and whenw1/2 then the rank ofC is at leastp. For the problem of approximating a givenn×n matrix with a zero diagonal by a squared-distance matrix, it is shown that the sstress criterion leads to a similar weighted least squares solution withw=(n+2)/4; the main result remains true. Other related problems and algorithmic consequences are briefly discussed.     

Differential ordering of objects and attributes

By reference to nominated attributes, a genus, being a population of objects of one specified kind, may be partitioned into species, being subpopulations of different kinds. A prototype is an object representative of its species within the genus. Using this framework, the paper describes how objects can be relatively differentiated with respect to attributes, and how attributes can be relatively differentiating with respect to objects. Methods and rationale for such differential ordering of objects and attributes are presented by example, formal development, and application.For a genus comprisingn species of object there is a subsetP ofn distinct prototypes. With respect tom nominated attributes, each object in has anm-element characterization. Together these determine ann ×m objects × attributes matrix, the rows of which are the characterizations of the prototypical objects. Over then species in , an associated relative frequency vector gives the distribution of objects (and of their characterizations). The matrix and vector associate the objects in with points in a metric space (P, ); and it is with respect to various sums of distances in this attribute space that one can differentially order objects and attributes.The definition of the distance function is generalized across kinds of difference, types of characterization, scale-types of measurement, Minkowskiindex 1, and any form of distribution of objects over species. Explanatory and taxonomic applications in psychology and other fields are discussed, with focus on classification, identification, recognition, and search. The Braille code and the identification of its characters provide illustration.An anticipation and some preliminary indications were given in Sutcliffe and Bristow (1966), Sutcliffe (1972, 1973), and Nowakowska (1975). Subsequently the ideas have been extended and their applications realized in a computer program which, in its development, has so far gone through many minor and three major revisions to its present form in Sutcliffe (1985). The foregoing provided the foundation for the empirical applications and for the presentation in this paper of the ideas in their general form. the research has been supported by funds from the University of Sydney Research Grant and from the Australian Research Grants Scheme. In the working out and exposition of the ideas I have very much benefited from constructive critical comment given by C. R. Latimer, J. B. Michell, G. Oliphant, and E. Seneta, and from the professional programming skills of Michael Wilson and David Shillito. I am grateful for the invitation and the facilities for writing extended during 1983 by Georges Noizet, Laboratoire de Psychologie Expérimentale, Université René Descartes, Paris V, and by Samuel Messick, Vice President for Research, E.T.S. Princeton, N.J. Finally, I acknowledge the improvements in presentation of this paper which have arisen from the editor's and reviewers' comments.     

Student-teacher concordance on dimensions of student social competence: A multitrait-multimethod analysis

Teacher and self-ratings of social competence were obtained for 669 (341 males, 328 females) grades 3–6 students using the Social Behavior Assessment—Revised (SBA-R) and a self-report scale consisting of the identical items reworded in first person. Factor analysis and multitrait-multimethod matrix analysis were used to validate construct interpretations. The previous four-factor structure of the SBA-R was not replicated. However, the three-factor structure that did emerge was better defined. Although student-teacher concordance was moderate for the Self-Control/Social Convention and Academic Responsibility factors, it was minimal for the Social Participation factor. Evidence of discriminant validity was weak. As with other studies using rating scales, method bias was in evidence. Sex differences were found in terms of variance explained by each factor and convergent validity. Discussion focuses on problems associated with construct validation in general and validation of school-related social competence in particular.     

A sequential cognitive diagnosis model for polytomous responses

This paper proposes a general polytomous cognitive diagnosis model for a special type of graded responses, where item categories are attained in a sequential manner, and associated with some attributes explicitly. To relate categories to attributes, a category‐level Q‐matrix is used. When the attribute and category association is specified a priori, the proposed model has the flexibility to allow different cognitive processes (e.g., conjunctive, disjunctive) to be modelled at different categories within a single item. This model can be extended for items where categories cannot be explicitly linked to attributes, and for items with unordered categories. The feasibility of the proposed model is examined using simulated data. The proposed model is illustrated using the data from the Trends in International Mathematics and Science Study 2007 assessment.     

Fungible Correlation Matrices: A Method for Generating Nonsingular,Singular, and Improper Correlation Matrices for Monte Carlo Research

For a fixed set of standardized regression coefficients and a fixed coefficient of determination (R-squared), an infinite number of predictor correlation matrices will satisfy the implied quadratic form. I call such matrices fungible correlation matrices. In this article, I describe an algorithm for generating positive definite (PD), positive semidefinite (PSD), or indefinite (ID) fungible correlation matrices that have a random or fixed smallest eigenvalue. The underlying equations of this algorithm are reviewed from both algebraic and geometric perspectives. Two simulation studies illustrate that fungible correlation matrices can be profitably used in Monte Carlo research. The first study uses PD fungible correlation matrices to compare penalized regression algorithms. The second study uses ID fungible correlation matrices to compare matrix-smoothing algorithms. R code for generating fungible correlation matrices is presented in the supplemental materials.