An intrasubject approach to causal attribution

The present investigation draws on the judgment research tradition in order to examine the causal attributions made by individual subjects in an often used attribution task. Formal empirical tests of Kelley's (1967) attribution theory have demonstrated that attributions are influenced by the interaction of consensus, distinctiveness, and consistency information. None of these studies, however, have separately examined attributions made by individual judges. Implicit assumptions about individual differences, for example, have been made by the template-matching model of causal attribution (Orvis, Cunningham, & Kelley, 1975) but have not been scrutinized at the intrasubject level. Log linear modeling of attributions in the present research showed that while subjects were influenced by the causal information in the task, the relation between this information and attributions was more importantly characterized by individual differences than by uniform patterning. The nature of these individual differences and the significance of an idiographic approach to causal analysis are discussed.     

Applications of multivariate visualization to behavioral sciences

The complexity of psychological science often requires the collection and analysis of multidimensional data. Such data bring about a corresponding cognitive load that has led scientists to develop techniques of scientific visualization to ease the burden. This paper provides an introduction to scientific visualization techniques, a framework for understanding those techniques, and an assessment of the suitability of this approach for psychology. The framework employed builds on the notion of balancingnoise andsmooth in statistical analysis.     

High-performance computer applications in the behavioral sciences

This symposium revisited the 1985 conference on Advanced Computing for Psychology. That meeting examined the application of new supercomputers in the behavioral sciences. The present symposium reviewed high-performance computing as applied to psychological models, human vision, neuralphysiological processes, and statistical analysis. The recent past and the projected future of high-performance computing in the behavioral sciences were evaluated.     

Feature inference and the causal structure of categories

The purpose of this article was to establish how theoretical category knowledge-specifically, knowledge of the causal relations that link the features of categories-supports the ability to infer the presence of unobserved features. Our experiments were designed to test proposals that causal knowledge is represented psychologically as Bayesian networks. In five experiments we found that Bayes' nets generally predicted participants' feature inferences quite well. However, we also observed a pervasive violation of one of the defining principles of Bayes' nets-the causal Markov condition-because the presence of characteristic features invariably led participants to infer yet another characteristic feature. We argue that this effect arises from a domain-general bias to assume the presence of underlying mechanisms associated with the category. Specifically, people take an exemplar to be a "well functioning" category member when it has most or all of the category's characteristic features, and thus are likely to infer a characteristic value on an unobserved dimension.     

The role of causal models in analogical inference

Computational models of analogy have assumed that the strength of an inductive inference about the target is based directly on similarity of the analogs and in particular on shared higher order relations. In contrast, work in philosophy of science suggests that analogical inference is also guided by causal models of the source and target. In 3 experiments, the authors explored the possibility that people may use causal models to assess the strength of analogical inferences. Experiments 1-2 showed that reducing analogical overlap by eliminating a shared causal relation (a preventive cause present in the source) from the target increased inductive strength even though it decreased similarity of the analogs. These findings were extended in Experiment 3 to cross-domain analogical inferences based on correspondences between higher order causal relations. Analogical inference appears to be mediated by building and then running a causal model. The implications of the present findings for theories of both analogy and causal inference are discussed.     

NSF programs in the behavioral and neural sciences

The National Science Foundation’s new Division of Behavioral and Neural Sciences supports basic research and related activities in psychology, ethology, anthropology, linguistics, and the neurosciences. Research equipment and facilities can be provided either through a grant supporting a research project or through a separate grant. The scientific importance and soundness of the research to be conducted, as evaluated by reviewers from the research community, are the main criteria for support. Preparation of proposals is briefly discussed, and sources of further information are noted.     

Automated problem solving for the behavioral sciences

In view of the obvious advantages of computers for the behavioral sciences, the question is raised as to how to make more effective use of computing capabilities. One idea is to require that fledgling behavioral scientists receive brief training in flowcharting and algorithm generation rather than a full course in computing skills. Such training would be an important adjunct for those who would go on for further instruction, especially in view of current deficiencies in many computer courses. One recurrent deficiency lies in the lack of specific guidelines for conceptualizing problems for computer implementation. Such guidelines are developed here, along with other suggestions designed to attenuate the difficulty in conceptualization.     

Psychology,behavioral sciences,and the challenge to medical education

It is generally agreed that the health care system is in crisis despite reform efforts over the past two decades. Evidence is presented which suggests that medical education has failed successfully to integrate medically relevant behavioral science research findings into medical school curricula or train physicians in the application of behaviorally based treatment technologies. Psychologists in medical education settings have the opportunity to impact medical education and foster psychology's role in health care. If psychology fails to respond to this opportunity, we cannot then complain of the inevitable consequences.An earlier version of this paper was presented at the annual meeting of the American Association of Medical Colleges, Washington, DC, November 1993.