Two interpretations of the discrimination parameter

In this paper we propose two interpretations for the discrimination parameter in the two-parameter logistic model (2PLM). The interpretations are based on the relation between the 2PLM and two stochastic models. In the first interpretation, the 2PLM is linked to a diffusion model so that the probability of absorption equals the 2PLM. The discrimination parameter is the distance between the two absorbing boundaries and therefore the amount of information that has to be collected before a response to an item can be given. For the second interpretation, the 2PLM is connected to a specific type of race model. In the race model, the discrimination parameter is inversely related to the dependency of the information used in the decision process. Extended versions of both models with person-to-person variability in the difficulty parameter are considered. When fitted to a data set, it is shown that a generalization of the race model that allows for dependency between choices and response times (RTs) is the best-fitting model.     

Simultaneous classification and multidimensional scaling with external information

For the exploratory analysis of a matrix of proximities or (dis)similarities between objects, one often uses cluster analysis (CA) or multidimensional scaling (MDS). Solutions resulting from such analyses are sometimes interpreted using external information on the objects. Usually the procedures of CA, MDS and using external information are carried out independently and sequentially, although combinations of two of the three procedures (CA and MDS, or multidimensional scaling and using external information) have been proposed in the literature. The present paper offers a procedure that combines all three procedures in one analysis, using a model that describes a partition of objects with cluster centroids represented in a low-dimensional space, which in turn is related to the information in the external variables. A simulation study is carried out to demonstrate that the method works satisfactorily for data with a known underlying structure. Also, to illustrate the method, it is applied to two empirical data sets.     

Winnicott, Balint, and the Independent Tradition

This article compares and contrasts two main aspects of the work of Winnicott and Balint: their theories of infantile development and their theoretical and clinical work on the use of regression as a therapeutic agent. The relationship of their thinking to aspects of the British Independent Group's theories and clinical work is noted vis-à-vis the basic acceptance of classical theory and technique, acknowledgment and use of some of Klein's contributions, the influence of trauma and the external environment on psychic development and psychopathology, the importance of holding and the setting, and the reintegration of previously split off and lost parts of the self.     

Breaking the Solid Ground of Common Sense: Undoing “Structure” with Michael Balint

Balint's great merit was to question what, in the classical perspective, was assumed as a prerequisite for analysis and thus located beyond analysis: the maturity of the ego. A fundamental premise of his work was Ferenczi's distrust for the structural model, which praised the maturity of the ego and its verbal, social, and adaptive abilities. Ferenczi's view of ego maturation as a trauma derivative was strikingly different from the theories of all other psychoanalytic schools and seems to be responsible for Balint's understanding of regression as a sort of inverted process that enables the undoing of the sheltering structures of the mature mind. Balint's understanding of the relation between mature ego and regression diverged not only from the ego psychologists, who emphasized the idea of therapeutic alliance, but also from most of the authors who embraced the object-relational view, like Klein (who considered regression a manifestation of the patient's craving for oral gratification), Fairbairn (who gave up the notion of regression), and Guntrip (who viewed regression as a schizoid phenomenon related to the ego weakness). According to Balint, the clinical appearance of a regression would depend also on the way the regression is recognized, is accepted, and is responded to by the analyst. In this respect, his position was close to Winnicott's reformulation of the therapeutic action. Yet, the work of Balint reflects the persuasion that the progressive fluidification of the solid structure could be enabled only by the analyst's capacity for becoming himself or herself [unsolid].     

不同年级学生阅读科技文章的眼动研究

本实验使用４２００Ｒ眼动仪对小学三年级、初二、高二和大学生阅读科技文章的眼动特征进行研究。结果发现;１．随年龄的提高,被试阅读课文的总注视次数显著减少;２．高年级学生能够根据阅读内容的重要性来灵活地调节自己的眼动策略;３．随着年级的提高,各年级被试使用前进式回视的比例逐渐减少,而使用选择式回视的比例逐渐增加。     

Data, model, conclusion, doing it again

This paper explores the robustness of conclusions from a statistical model against variations in model choice (rather than variations in random sampling and random assignment to treatments, which are the usual variations covered by inferential statistics). After the problem formulation in section 1, section 2 presents an example from Box and Tiao in which variation in parent distribution is modeled for a one sample location problem. An adaptive Bayesian procedure permits to use a weighted mixture of parent distributions rather than choosing just one, such as a normal or a uniform distribution.In section 3 similar considerations are applied to an event history model for the influence of education and gender on age at first marriage, but here the conclusions are hardly influenced by the choice of the duration distribution. In section 4 a brief discussion of model choice in factor analysis and structural equation models is followed by a more elaborate treatment of the choice of integer valued slopes for item response functions in the OPLM model which is an extension of the Rasch model. A modest simulation study suggests that Adaptive Bayesian Modeling with a mixture of sets of slopes works better than fixing one set of postulated slopes.The paper concludes with some remarks on the roles and sources of prior distributions followed by a short epilogue which argues that simultaneous consideration of a class of models for the same data is sometimes superior to exclusively analyzing the data under one specific model chosen from such a class.This article is based on the Presidential Address Ivo W. Molenaar gave on June 20, 1998 at the 1998 Annual Meeting of the Psychometric Society held at the University of Illinois in Champaign, Illinois. Thanks is given to John Wiley & Sons and George C. Tiao for granting permission to reprint three figures from the book George C. Tiao wrote with George E. P. Box titled Bayesian Inference in Statistical Analysis.—EditorThanks are due to Anne Boomsma, Jeffrey Hoogland, Mark Huisman, Tom Snijders, Marijtje Van Duijn, and Norman Verhelst for suggesting improvements and/or assisting with data analyses.     

Linear relations amongk sets of variables

A family of solutions for linear relations amongk sets of variables is proposed. It is shown how these solutions apply fork=2, and how they can be generalized from there tok3.The family of solutions depends on three independent choices: (i) to what extent a solution may be influenced by differences in variances of components within each set; (ii) to what extent the sets may be differentially weighted with respect to their contribution to the solution—including orthogonality constraints; (iii) whether or not individual sets of variables may be replaced by an orthogonal and unit normalized basis.Solutions are compared with respect to their optimality properties. For each solution the appropriate stationary equations are given. For one example it is shown how the determinantal equation of the stationary equations can be interpreted.     

The asymptotic distribution of commonality components

Commonality components have been defined as a method of partitioning squared multiple correlations. In this paper, the asymptotic joint distribution of all 2 ^k – 1 squared multiple correlations is derived. The asymptotic joint distribution of linear combinations of squared multiple correlations is obtained as a corollary. In particular, the asymptotic joint distribution of commonality components are derived as a special case. Simultaneous and nonsimultaneous asymptotic confidence intervals for commonality components can be obtained from this distribution.This work was supported in part by the Spencer Foundation and the National Science Foundation.The authors are grateful to Bryna Siegel-Gorlick for her help in obtaining the data used in Example 4.3, and to the referees for their comments and suggestions.     

Openness relates to COVID-19 vaccination rates across 48 United States but politics trump personality

Does geographic variation in personality across the United States relate to COVID-19 vaccination rates? To answer this question, we combined multiple state-level datasets: (a) Big Five personality averages (i.e., extraversion, agreeableness, conscientiousness, neuroticism, and openness; Rentfrow et al., 2008), (b) COVID-19 full-vaccination rates (CDC, 2021a), (c) health-relevant demographic covariates (population density, per capita gross domestic product, and racial/ethnic data; Webster et al., 2021), and (d) political and religiosity data. Analyses showed openness as the strongest correlate of full-vaccination rates (r = 0.51). Controlling for other traits, demographic covariates, and spatial dependence, openness remained significantly related to full-vaccination rates (r_p = 0.55). Adding political and religiosity data to this model diminished openness effects for full-vaccination rates to non-significance (r_p = 0.26); however, extraversion emerged as a significant correlate of full-vaccination rates (r_p = 0.37). Although politics are paramount, we suspect that states with higher average openness scores are more conducive to novel thinking and behavior—dispositions that may be crucial in motivating people to take newly-developed vaccines based on new technologies to confront a novel coronavirus.     

The Unreal Child1

Unrepresented mental states lead to an impaired ability to feel emotions and trust in oneself, one’s history and in the world. The article explores the question of how representations of oneself and the relevant other, the mother, become possible in the course of therapy when dissociative processes previously made this impossible, and what role unconscious communication plays in the analytic realm. This question will be explored by examining the theories of André Green, Philip Bromberg, and Howard Levine.