Nodal structure and the partitioning of equivalence classes

By definition, all of the stimuli in an equivalence class have to be functionally interchangeable with each other. The present experiment, however, demonstrated that this was not the case when using post-class-formation dual-option response transfer tests. With college students, two 4-node 6-member equivalence classes with nodal structures of A-->B-->C-->D-->E-->F were produced by training AB, BC, CD, DE, and EF. Then, unique responses were trained to the C and D stimuli in each class. The responses trained to C generalized to B and A, while the responses trained to D generalized to E and F. Thus, each 4-node 6-member equivalence class was bifurcated into two 3-member functional classes: A-->B-->C and D-->E-->F, with class membership precisely predicted by nodal structure. A final emergent relations test documented the intactness of the underlying 4-node 6-member equivalence classes. The coexistence of the interchangeability of stimuli in an equivalence class and the bifurcation of such a class in terms of nodal structure was explained in the following manner. The conditional discriminations that are used to establish a class also imposes a nodal structure on the stimuli in the class. Thus, the stimuli in the class acquire two sets of relational properties. If the format of a test trial allows only one response option per class, responding on those trials will be in accordance with class membership and will not express the effects of nodal distance. If the format of a test trial allows more than one response option per class, responding on those trials will be determined by the nodal structure of the class. Thus, the relational properties expressed by the stimuli in an equivalence class are determined by the discriminative function served by the format of a test trial.     

Bayesian Hierarchical Classes Analysis

Hierarchical classes models are models for N-way N-mode data that represent the association among the N modes and simultaneously yield, for each mode, a hierarchical classification of its elements. In this paper we present a stochastic extension of the hierarchical classes model for two-way two-mode binary data. In line with the original model, the new probabilistic extension still represents both the association among the two modes and the hierarchical classifications. A fully Bayesian method for fitting the new model is presented and evaluated in a simulation study. Furthermore, we propose tools for model selection and model checking based on Bayes factors and posterior predictive checks. We illustrate the advantages of the new approach with applications in the domain of the psychology of choice and psychiatric diagnosis. Iwin Leenen is now at the Instituto Mexicano de Investigación de Familia y Población (IMIFAP), Mexico. The research reported in this paper was partially supported by the Spanish Ministerio de Educación y Ciencia (programa Ramón y Cajal) and by the Research Council of K.U.Leuven (PDM/99/037, GOA/2000/02, and GOA/2005/04). The authors are grateful to Johannes Berkhof for fruitful discussions.     

On the equivalence between elimination-by-aspects and generalised extreme value models of choice behaviour

Elimination-by-aspects and generalised extreme value offer competing paradigms for the representation of a common behaviour, that of individual discrete choice. Observing certain consistencies in their mathematical structure, several eminent authors have commented on the degree of equivalence between the two paradigms. Most contributions to this debate have, however, been less than definitive. More fundamentally, the contributions lack consensus. We advance the debate by establishing formal mathematical conditions under which three-alternative tree models from the two paradigms are exactly equivalent. We then extend our analysis to consider more general models, showing that equivalence can be established for general tree models, but not for cross-nested models.     

Current status of the motor program: Revisited

The motor program is a concept that has had a major influence on theorizing in the field of motor control. However, there has been a lack of consensus as to what exactly is a motor program and its role in movement organization and execution. In 1994 Morris, Summers, Matyas, and Iansek concluded from a review of the application of the motor program concept in the field of physical therapy that continued use of the term may impede progress in the field. In this paper we examine what has happened to the motor program concept in the thirteen years since the previous evaluation. The review indicates that although the term is still being used in different ways, the theoretical existence of a motor program appears to be generally accepted by researchers in experimental psychology, movement science, and neurophysiology. The recent development of powerful brain imaging techniques may allow determination of whether the motor program should be regarded as a metaphorical or literal concept.     

Labels as features (not names) for infant categorization: a neurocomputational approach

A substantial body of experimental evidence has demonstrated that labels have an impact on infant categorization processes. Yet little is known regarding the nature of the mechanisms by which this effect is achieved. We distinguish between two competing accounts: supervised name-based categorization and unsupervised feature-based categorization. We describe a neurocomputational model of infant visual categorization, based on self-organizing maps, that implements the unsupervised feature-based approach. The model successfully reproduces experiments demonstrating the impact of labeling on infant visual categorization reported in Plunkett, Hu, and Cohen (2008) . It mimics infant behavior in both the familiarization and testing phases of the procedure, using a training regime that involves only single presentations of each stimulus and using just 24 participant networks per experiment. The model predicts that the observed behavior in infants is due to a transient form of learning that might lead to the emergence of hierarchically organized categorical structure and that the impact of labels on categorization is influenced by the perceived similarity and the sequence in which the objects are presented. The results suggest that early in development, say before 12 months old, labels need not act as invitations to form categories nor highlight the commonalities between objects, but they may play a more mundane but nevertheless powerful role as additional features that are processed in the same fashion as other features that characterize objects and object categories.     

Community types and mental health: a multilevel study of local environmental stress and coping

Research has found that neighborhood structural characteristics can influence residents' mental health. Few studies, however, have explored the proximal reasons behind such influences. This study investigates how different types of communities, in terms of environmental stressors (social and physical disorder and fear of crime) and social resources (informal ties and formal organizational participation), affect well-being, depression, and anxiety in adult residents. Data are from a survey of 412 residents nested in 50 street blocks. Block stressors and resources were cluster analyzed to identify six block types. After controlling for several individual- and block-level characteristics, results from multilevel models suggest that in communities facing relatively few stressors, higher levels of formal participation are associated with better mental health. Because high levels of formal participation were not found in communities with higher levels of stressors, the impact of participation in such contexts could not be examined. However, results suggest that in communities where stressors are more common, isolation from neighbors may have a protective effect on mental health.     

A general method for computing hierarchical component structures by Goldberg’s Bass-Ackwards method

Goldberg [Goldberg, L. R.(in press) Doing it all Bass-Ackwards: The development of hierarchical factor structures from the top down. Journal of Research in Personality] has recently described a novel method for computing hierarchical component structures via a “top down” design. He calls his method the “Bass Ackwards” approach to distinguish it from more common “bottom up” methods for obtaining hierarchical solutions. Using simple matrix equations, in this commentary I demonstrate that the end result of a Bass Ackwards analysis—that is, the correlations between component scores from different levels of a hierarchy—can be calculated without calculating the actual component scores. By avoiding component-score calculation, Goldberg’s method (a) can be applied to any data set in which a correlation matrix is available, and (b) can be applied to factor scores rather than estimated factor scores. Goldberg suggests that the Bass Ackwards method represents a useful tool for elucidating the underlying dimensionality and latent structure (rotation in hyperspace) of a data set. Computer code is reported in the Appendix A of this article to help personality researchers more fully evaluate this claim in empirical and simulated data.     

Trait anhedonia is a transdiagnostic correlate of internalizing problems during adolescence

Developmental research documents that anhedonia, or diminished interest in usual activities, is associated with a diverse array of emotional problems in childhood and adolescence. Meanwhile, official nosologies desginate anhedonia as a more specific characteristic of major depressive disorder. Using a quantitative model of the internalizing domain, we compared the strength of transdiagnostic versus diagnosis-specific pathways from anhedonia to major depression (and other internalizing conditions) during adolescence. We recruited 241 youth ages 14–17 who completed semistructured interviews of anxiety and depressive disorders, as well as several self-report surveys of trait anhedonia and neuroticism. Confirmatory factor analysis of diagnostic correlations revealed good fit for a unidimensional model of the 10 internalizing conditions we assessed. This overarching internalizing dimension was statistically significantly correlated with trait anhedonia (r = 0.17) and neuroticism (r = 0.59). In contrast, anhedonia was virtually unrelated to major depression (r = −0.02), net the internalizing dimension. Thus, in this sample, the connection between anhedonia and major depression was explained by a transdiagnostic dimension presumed to underlie all internalizing problems. Compared to neuroticism, however, anhedonia had a more limited association with internalizing, consistent with established personality models of anxiety and depression. We conclude that these data are consistent with conceptualizing anhedonia predominantly as a transdiagnostic correlate of internalizing conditions, rather than a specific marker of major depression, in developmental psychopathology research and clinical interventions for young people.     

Relations between baseline contingencies and equivalence probe performances

Following the emergence of two three-member equivalence classes (A1B1C1 and A2B2C2), 5 college students were exposed to one or more changes in the reinforcement contingencies controlling baseline conditional discriminations. AC relations were either reversed (i.e., C2 was reinforced and C1 punished when A1 was the sample; C1 was reinforced and C2 punished when A2 was the sample) or arranged randomly (i.e., C2 and C1 were reinforced and punished equally often in the presence of A1 and A2). In a third condition, the original AB and AC relations were reversed. Results showed that although baseline conditional discrimination performances were under the control of reinforcement contingencies, and performances on symmetry trials varied with baseline responding for 3 of 4 subjects when contingencies were reversed, performances on transitivity probes remained consistent with the initial equivalence class. These inconsistencies between probe and baseline performances were striking because conditional discriminations are thought to be the determinants of equivalence class performance. Similarly, the contrast between performances on symmetry and transitivity probes was of theoretical interest because equivalence classes are defined by congruent patterns of responding on probe trials.     

Projection of a binary criterion into a model of hierarchical classes

A formal analysis is made of how to project an attribute criterion into the hierarchical classes model for object by attribute data proposed by De Boeck and Rosenberg. The projection is conceptualized as the prediction of the attribute criterion by means of a logical rule defined on the basis of attribute combinations from the model. Eliminative and constructive strategies are proposed to find logical rules with maximal predictive power and minimal formula complexity. Logical analyses of a real data set are reported and compared with a logistic regression to demonstrate the usefulness of the logical strategies, and to show the complementarity of logical and probabilistic approaches.The first suthor is Senior Research Assistant of the National Fund for Scientific Research (Belgium). We would like to thank the Editor, the reviewers, Seymour Rosenberg, and Luc Delbeke for their helpful comments on earlier drafts of this article.