This article advances a simple conception of test validity: A test is valid for measuring an attribute if (a) the attribute exists and (b) variations in the attribute causally produce variation in the measurement outcomes. This conception is shown to diverge from current validity theory in several respects. In particular, the emphasis in the proposed conception is on ontology, reference, and causality, whereas current validity theory focuses on epistemology, meaning, and correlation. It is argued that the proposed conception is not only simpler but also theoretically superior to the position taken in the existing literature. Further, it has clear theoretical and practical implications for validation research. Most important, validation research must not be directed at the relation between the measured attribute and other attributes but at the processes that convey the effect of the measured attribute on the test scores. We start this article with a request to the reader. Please take a slip of paper and write down your definition of the term construct validity. Now, take the classic article of Cronbach and Meehl (1955), who invented the concept, and a more recent authoritative article on validity, for instance that of Messick (1989), and check whether you recognize your definition in these works. You are

This paper analyzes the theoretical, pragmatic, and substantive factors that have hampered the integration between psychology and psychometrics. Theoretical factors include the operationalist mode of thinking which is common throughout psychology, the dominance of classical test theory, and the use of “construct validity ” as a catch-all category for a range of challenging psychometric problems. Pragmatic factors include the lack of interest in mathematically precise thinking in psychology, inadequate representation of psychometric modeling in major statistics programs, and insufficient mathematical training in the psychological curriculum. Substantive factors relate to the absence of psychological theories that are sufficiently strong to motivate the structure of psychometric models. Following the identification of these problems, a number of promising recent developments are discussed, and suggestions are made to further the integration of psychology and psychometrics.

Knowledge-based systems are computer programs achieving expert-level competence in solving problems for specific task areas. This chapter is a tutorial on the implementation of this kind of systems in the framework of credal networks. Credal networks are a generalization of Bayesian networks where credal sets, i.e., closed convex sets of probability measures, are used instead of precise probabilities. This allows for a more flexible model of the knowledge, which can represent ambiguity, contrast and contradiction in a natural and realistic way. The discussion guides the reader through the different steps involved in the specification of a system, from the evocation and elicitation of the knowledge to the interaction with the system by adequate inference algorithms. Our approach is characterized by a sharp distinction between the domain knowledge and the process linking this knowledge to the perceived evidence, which we call the observational process. This distinction leads to a very flexible representation of both domain knowledge and knowledge about the way the information is collected, together with a technique to aggregate information coming from different sources. The overall procedure is illustrated throughout the chapter by a simple knowledge-based system for the prediction of the result of a football match.

In their review of validity of the Implicit Association Test and affective priming, J. De Houwer,

Abstract not found

Abstract—We describe a novel learning scheme for hidden dependencies in video streams. The proposed scheme aims to transform a given sequential stream into a dependency structure of particle populations. Each particle population summarizes an associated segment. The novel point of the proposed scheme is that both of dependency learning and segment summarization are performed in an unsupervised online manner without assuming priors. The proposed scheme is executed in two-stage learning. At the first stage, a segment corresponding to a common dominant image is estimated using evolutionary particle filtering. Each dominant image is depicted based on combinations of image descriptors. Prevailing features of a dominant image are selected through evolution. Genetic operators introduce the essential diversity preventing sample impoverishment. At the second stage, transitional probability between the estimated segments is computed and stored. The proposed scheme is applied to extract dependencies in an episode of a TV drama. We demonstrate performance by comparing to human estimations.

Abstract not found

Abstract: This article provides the first test of an adaptationist ‘common calibration ’ theory to explain the origins of trait covariation, which holds that (i) personality traits are often facultatively calibrated in response to cues that ancestrally predicted the reproductive payoffs of different trait levels and (ii) distinct traits that are calibrated on the basis of common input cues will exhibit consistent patterns of covariation. This theory is applied to explain the covariation within a ‘personality syndrome ’ encompassing various interpersonal trait dimensions (e.g. extraversion, emotionality and attachment styles). Specifically, it is hypothesized that these traits are inter-correlated because each is calibrated in response to relative bargaining power (RBP)—a joint function of one’s ability to benefit others and harm others. Path analyses from a correlational study compellingly supported this theoretical model: Objective and self-perceived measures of RBP-enhancing phenotypic features (physical attractiveness and physical strength) influenced an internal regulatory variable indexing RBP (i.e. self-perceived RBP), which in turn had robust effects on each of the focal personality traits. Moreover, in support of the theory’s core postulate, controlling for selfperceived RBP greatly reduced the covariation within the interpersonal syndrome. These novel findings illustrate the promise of an evolutionary psychological approach to elucidating trait covariation. Copyright © 2013 John Wiley & Sons, Ltd. Key words: behavioural syndrome; evolutionary psychology; facultative calibration; internal regulatory variable;

An important, sometimes controversial feature of all psychological phenomena is whether they are categorical or dimensional. A conceptual and psychometric framework is described for distinguishing whether the latent structure behind manifest categories (e.g., psychiatric diagnoses, attitude groups, or stages of development) is category-like or dimension-like. Being dimension-like requires (a) withincategory heterogeneity and (b) between-category quantitative differences. Being category-like requires (a) within-category homogeneity and (b) between-category qualitative differences. The relation between this classification and abrupt versus smooth differences is discussed. Hybrid structures are possible. Being category-like is itself a matter of degree; the authors offer a formalized framework to determine this degree. Empirical applications to personality disorders, attitudes toward capital punishment, and stages of cognitive development illustrate the approach. In this article we describe a conceptual and psychometric scheme for distinguishing the categorical versus dimensional nature of psychological variables. By psychological variables we mean variables used to distinguish between entities in some psychological respect. These entities are commonly persons, but they

Abstract not found