Sweet's syndrome with arthritis in an 8-month-old boy

Sweet's syndrome was diagnosed in a 4-month-old boy. He was successfully treated with systemic corticosteroids. At the age of 8 months, he developed acute arthritis in his right knee. The synovial fluid was analyzed and revealed a very high neutrophil count and neutrophil activation with a detectable level of intraarticular granulocyte-monocyte colony stimulating factor (GM-CSF). Prednisone injection into the knee led to dramatic improvement. No recurrence occurred. Although arthritis and/or arthralgia are common features in adult patients with Sweet's syndrome, this is the first reported case of Sweet's arthritis in a child.     

A nonlinear mixed model framework for item response theory.

Mixed models take the dependency between observations based on the same cluster into account by introducing 1 or more random effects. Common item response theory (IRT) models introduce latent person variables to model the dependence between responses of the same participant. Assuming a distribution for the latent variables, these IRT models are formally equivalent with nonlinear mixed models. It is shown how a variety of IRT models can be formulated as particular instances of nonlinear mixed models. The unifying framework offers the advantage that relations between different IRT models become explicit and that it is rather straightforward to see how existing IRT models can be adapted and extended. The approach is illustrated with a self-report study on anger. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Feelings change: Accounting for individual differences in the temporal dynamics of affect.

People display a remarkable variability in the patterns and trajectories with which their feelings change over time. In this article, we present a theoretical account for the dynamics of affect (DynAffect) that identifies the major processes underlying individual differences in the temporal dynamics of affective experiences. It is hypothesized that individuals are characterized by an affective home base, a baseline attractor state around which affect fluctuates. These fluctuations vary as the result of internal or external processes to which an individual is more or less sensitive and are regulated and tied back to the home base by the attractor strength. Individual differences in these 3 processes—affective home base, variability, and attractor strength—are proposed to underlie individual differences in affect dynamics. The DynAffect account is empirically evaluated by means of a diffusion modeling approach in 2 extensive experience-sampling studies on people's core affective experiences. The findings show that the model is capable of adequately capturing the observed dynamics in core affect across both large (Study 1) and shorter time scales (Study 2) and illuminate how the key processes are related to personality and emotion dispositions. Implications for the understanding of affect dynamics and affective dysfunctioning in psychopathology are also discussed. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Hierarchical diffusion models for two-choice response times.

Two-choice response times are a common type of data, and much research has been devoted to the development of process models for such data. However, the practical application of these models is notoriously complicated, and flexible methods are largely nonexistent. We combine a popular model for choice response times—the Wiener diffusion process—with techniques from psychometrics in order to construct a hierarchical diffusion model. Chief among these techniques is the application of random effects, with which we allow for unexplained variability among participants, items, or other experimental units. These techniques lead to a modeling framework that is highly flexible and easy to work with. Among the many novel models this statistical framework provides are a multilevel diffusion model, regression diffusion models, and a large family of explanatory diffusion models. We provide examples and the necessary computer code. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Numerical integration in logistic-normal models

Marginal maximum likelihood estimation is commonly used to estimate logistic-normal models. In this approach, the contribution of random effects to the likelihood is represented as an intractable integral over their distribution. Thus, numerical methods such as Gauss-Hermite quadrature (GH) are needed. However, as the dimensionality increases, the number of quadrature points becomes rapidly too high. A possible solution can be found among the Quasi-Monte Carlo (QMC) methods, because these techniques yield quite good approximations for high-dimensional integrals with a much lower number of points, chosen for their optimal location. A comparison between three integration methods for logistic-normal models: GH, QMC, and full Monte Carlo integration (MC) is presented. It turns out that, under certain conditions, the QMC and MC method perform better than the GH in terms of accuracy and computing time.     

Predicting the duration of emotional experience: Two experience sampling studies.

The authors present 2 studies to explain the variability in the duration of emotional experience. Participants were asked to report the duration of their fear, anger, joy, gratitude, and sadness episodes on a daily basis. Information was further collected with regard to potential predictor variables at 3 levels: trait predictors, episode predictors, and moment predictors. Discrete-time survival analyses revealed that, for all 5 emotions under study, the higher the importance of the emotion-eliciting situation and the higher the intensity of the emotion at onset, the longer the emotional experience lasts. Moreover, a reappearance, either physically or merely mentally, of the eliciting stimulus during the emotional episode extended the duration of the emotional experience as well. These findings display interesting links with predictions within N. H. Frijda's theory of emotion, with the phenomenon of reinstatement (as studied within the domain of learning psychology), and with the literature on rumination. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

Mixed model estimation methods for the Rasch model

Mixed models take the dependency between observations based on the same person into account by introducing one or more random effects. After introducing the mixed model framework, it is explained, by taking the Rasch model as a generic example, how item response models can be conceptualized as generalized linear and nonlinear mixed models. Common estimation methods for generalized linear and nonlinear models are discussed. In a simulation study, the performance of four estimation methods is assessed for the Rasch model under different conditions regarding the number of items and persons, and the degree of interindividual differences. The estimation methods included in the study are: an approximation of the integral over the random effect by means of Gaussian quadrature; direct maximization with a sixth-order Laplace approximation to the integrand; a linearized approximation of the nonlinear model employing PQL2; and finally a Bayesian MCMC method. It is concluded that the estimation methods perform almost equally well, except for a slightly worse recovery of the variance parameter for PQL2 and MCMC.     

The relation between event processing and the duration of emotional experience.

An emotional experience can last for only a couple of seconds up to several hours or even longer. In the present study, we examine to which extent covert intrapersonal actions (cognitions both related and unrelated to the emotion-eliciting stimulus) as well as overt interpersonal actions (social sharing) account for this variability in emotion duration. Participants were asked to report the duration of their anger, sadness, joy, and gratitude episodes on a daily basis during five days. Furthermore, information was collected with regard to their cognitions during the episodes and their social sharing behavior. Discrete-time survival analyses revealed that for three of the four emotions under study, stimulus-related cognitions with the same valence as the emotion lead to a prolongation of the episode; in contrast, both stimulus-related and stimulus-unrelated cognitions with a valence opposite to the emotion lead to a shortening. Finally, for the four emotions under study, social sharing was associated with a prolongation. The findings are discussed in terms of a possible process basis underlying the time dynamics of negative as well as positive emotions. (PsycINFO Database Record (c) 2011 APA, all rights reserved)     

Measuring needs with the Thematic Apperception Test: A psychometric study.

Three apperception theories that explain how people respond to Thematic Apperception Test cards are proposed: a simple apperception theory, an apperception theory with a dynamic component, and an apperception theory with 2 types of responses. Each theory is translated into an item response theory model and is applied to need for achievement (nAch) data. The analysis indicates that the best fitting model is provided by the apperception theory with 2 types of responses, also referred to as the drop-out apperception theory. The 1st type of response predicted by this theory is determined by the nAch level of the person and the achievement-response-eliciting value of the card; this response is diagnostic for the nAch level of the person. The 2nd type of response is not determined by the 2 aforementioned characteristics and is therefore not diagnostic of the person's nAch level. The results are cross-validated for need for power and need for affiliation. (PsycINFO Database Record (c) 2010 APA, all rights reserved)     

The effect of ignoring item interactions on the estimated discrimination parameters in item response theory.

Most item response theory models assume conditional independence, and it is known that interactions between items affect the estimated item discrimination. In this article, this effect is further investigated from a theoretical perspective and by means of simulation studies. To this end, a parametric model for item interactions is introduced. Next, it is shown that ignoring a positive interaction results in an overestimation of the discrimination parameter in the two-parameter logistic model (2PLM), whereas ignoring a negative interaction leads to an underestimation of the parameter. Furthermore, it is demonstrated that in some cases the item characteristic curves of the 2PLM and of an item involved in an interaction are quite similar, indicating that the 2PLM can provide a good fit to data with interactions. (PsycINFO Database Record (c) 2010 APA, all rights reserved)