Unidimensional factor models imply weaker partial correlations than zero-order correlations

In this paper we present a new implication of the unidimensional factor model. We prove that the partial correlation between two observed variables that load on one factor given any subset of other observed variables that load on this factor lies between zero and the zero-order correlation between these two observed variables. We implement this result in an empirical bootstrap test that rejects the unidimensional factor model when partial correlations are identified that are either stronger than the zero-order correlation or have a different sign than the zero-order correlation. We demonstrate the use of the test in an empirical data example with data consisting of fourteen items that measure extraversion.     

Tacit to explicit knowledge conversion

The ability to create, use and transfer knowledge may allow the creation or improvement of new products or services. But knowledge is often tacit: It lives in the minds of individuals, and therefore, it is difficult to transfer it to another person by means of the written word or verbal expression. This paper addresses this important problem by introducing a methodology, consisting of a four-step process that facilitates tacit to explicit knowledge conversion. The methodology utilizes conceptual modeling, thus enabling understanding and reasoning through visual knowledge representation. This implies the possibility of understanding concepts and ideas, visualized through conceptual models, without using linguistic or algebraic means. The proposed methodology is conducted in a metamodel-based tool environment whose aim is efficient application and ease of use.     

An Introduction to Network Psychometrics: Relating Ising Network Models to Item Response Theory Models

In recent years, network models have been proposed as an alternative representation of psychometric constructs such as depression. In such models, the covariance between observables (e.g., symptoms like depressed mood, feelings of worthlessness, and guilt) is explained in terms of a pattern of causal interactions between these observables, which contrasts with classical interpretations in which the observables are conceptualized as the effects of a reflective latent variable. However, few investigations have been directed at the question how these different models relate to each other. To shed light on this issue, the current paper explores the relation between one of the most important network models—the Ising model from physics—and one of the most important latent variable models—the Item Response Theory (IRT) model from psychometrics. The Ising model describes the interaction between states of particles that are connected in a network, whereas the IRT model describes the probability distribution associated with item responses in a psychometric test as a function of a latent variable. Despite the divergent backgrounds of the models, we show a broad equivalence between them and also illustrate several opportunities that arise from this connection.     

Changes in Behaviour and Body Weight Following a Single or Double Social Defeat in Rats

In a series of experiments, the consequences of a single and double social conflict on various behaviours and body weight in rats were studied. Animals were subjected to social defeat by placing them into the territory of an aggressive male conspecific for one hour, either once, or twice at the same time on two consecutive days. To assess the consequences of social defeat, three experiments were performed with independent groups of rats. In the first experiment, an open field test was performed two days after the last conflict. Locomotor activity was strongly reduced after social defeat. There were no differences between the single and double defeat group. To assess the effects of social defeat on subsequent social behaviour, a second experiment was performed in which experimental animals were confronted with an unfamiliar non-aggressive rat two days after a single or double conflict. Social defeat resulted in a reduction of social contact with the unfamiliar conspecific. There was no difference between the single and double conflict group. In the third experiment, the effects of social conflict on food intake, body weight and saccharine preference were measured. Food intake was not affected after a single conflict, but in the double conflict group food intake was decreased for several days. Body weight gain was decreased after both single and double social defeat. The decrease was stronger in the double conflict group. Water intake and saccharine preference were not significantly affected. This study revealed that social defeat in rats causes pronounced changes in various behaviours and body weight. Different aspects of behaviour are differentially affected by defeat with respect to the magnitude and time course of the changes induced. Moreover, different behavioural parameters are differentially sensitive to repetition of the stressor.