Nested Logit Models for Multiple-Choice Item Response Data

Nested logit item response models for multiple-choice data are presented. Relative to previous models, the new models are suggested to provide a better approximation to multiple-choice items where the application of a solution strategy precedes consideration of response options. In practice, the models also accommodate collapsibility across all distractor categories, making it easier to allow decisions about including distractor information to occur on an item-by-item or application-by-application basis without altering the statistical form of the correct response curves. Marginal maximum likelihood estimation algorithms for the models are presented along with simulation and real data analyses.     

Child Pornography Offending Seen Through Three Theoretical Lenses

Understanding the complex issues surrounding child pornography offending is still in its infancy, and questions regarding the etiological underpinnings of sexually deviant interests and behaviors for these offenders remain both salient and unanswered. This article considers these questions through the lenses of three psychological theories of behavior: (1) social learning theory, (2) courtship disorder theory, and (3) behavioral economics. The development and maintenance of child pornography offending, as well as the potential for off-line escalation of those behaviors, from each theoretical perspective is discussed and the implications for theoretically grounded clinical practice is explored.     

Toward a Social Psychology of Social Support

An analysis of social psychological aspects of social support examined several stages of the interaction between provider and recipient. In the first stage, the provider may offer support, respond positively to requests for support, or decline requests for support, whereas the recipient may seek, accept, or reject support. In the second stage, after support is exchanged, attributions about its effect may occur for each member, which in turn affects the extent to which the support is continued and the nature of its effect. Attributional errors about the effect may occur, especially if factors other than support—such as external factors—alter the problem status. The final stage follows the resolution of the problem and may involve reciprocation of support when roles are reversed, although such reciprocity may not be a necessary condition for social support. Possible mechanisms for both positive as well as negative effects of support were postulated. Assessing the effects of support is complicated by factors such as individual differences, the degree of match between social support beliefs held by provider and recipient, type of problem, and the timing of support.     

A unified approach to multiple‐set canonical correlation analysis and principal components analysis

Multiple‐set canonical correlation analysis and principal components analysis are popular data reduction techniques in various fields, including psychology. Both techniques aim to extract a series of weighted composites or components of observed variables for the purpose of data reduction. However, their objectives of performing data reduction are different. Multiple‐set canonical correlation analysis focuses on describing the association among several sets of variables through data reduction, whereas principal components analysis concentrates on explaining the maximum variance of a single set of variables. In this paper, we provide a unified framework that combines these seemingly incompatible techniques. The proposed approach embraces the two techniques as special cases. More importantly, it permits a compromise between the techniques in yielding solutions. For instance, we may obtain components in such a way that they maximize the association among multiple data sets, while also accounting for the variance of each data set. We develop a single optimization function for parameter estimation, which is a weighted sum of two criteria for multiple‐set canonical correlation analysis and principal components analysis. We minimize this function analytically. We conduct simulation studies to investigate the performance of the proposed approach based on synthetic data. We also apply the approach for the analysis of functional neuroimaging data to illustrate its empirical usefulness.     

The Effect of Interactivity on Learning Physical Actions in Virtual Reality

Virtual reality (VR) offers new possibilities for learning, specifically for training individuals to perform physical movements such as physical therapy and exercise. The current article examines two aspects of VR that uniquely contribute to media interactivity: the ability to capture and review physical behavior and the ability to see one's avatar rendered in real time from third person points of view. In two studies, we utilized a state-of-the-art, image-based tele-immersive system, capable of tracking and rendering many degrees of freedom of human motion in real time. In Experiment 1, participants learned better in VR than in a video learning condition according to self-report measures, and the cause of the advantage was seeing one's avatar stereoscopically in the third person. In Experiment 2, we added a virtual mirror in the learning environment to further leverage the ability to see oneself from novel angles in real time. Participants learned better in VR than in video according to objective performance measures. Implications for learning via interactive digital media are discussed.     

Wang Yangming and the Way of World Philosophy

This essay attempts to contextualize the importance of Wang Yangming’s 王陽明 philosophy in terms of world philosophy in the manner of Goethe’s innovative plan for “world literature” (Weltliteratur). China has the long history of philosophizing rather than non-philosophy contrary to the glaring and inexcusable misunderstanding of Hegel the Eurocentric universalist or monist. In today’s globalizing world of multicultural pluralism, ethnocentric universalism has become outdated and outmoded. Transversality, which is at once intercultural, interspecific, interdisciplinary, and intersensorial, is a far more befitting response than universality. In this context, what is focused and emphasized in Wang’s world philosophy is mainly fourfold. First, there is the unity or circularity of knowledge and action, that is, knowledge is the beginning of action, and action is the consummation of knowledge. Second, sincerity is the moral soul of Sinism as it is the enabling act of making perform all other virtues, including ren 仁. Third, in Sinism, including Wang’s philosophy, there is no Cartesian dualism in that the mind and the body are inseparable soulmates. Fourth, if ethics is prima philosophia, then geophilosophy is ultima philosophia to sustain and perpetuate all life-forms on earth (geo).     

Multilevel models for multiple-baseline data: modeling across-participant variation in autocorrelation and residual variance

Multilevel models (MLM) have been used as a method for analyzing multiple-baseline single-case data. However, some concerns can be raised because the models that have been used assume that the Level-1 error covariance matrix is the same for all participants. The purpose of this study was to extend the application of MLM of single-case data in order to accommodate across-participant variation in the Level-1 residual variance and autocorrelation. This more general model was then used in the analysis of single-case data sets to illustrate the method, to estimate the degree to which the autocorrelation and residual variances differed across participants, and to examine whether inferences about treatment effects were sensitive to whether or not the Level-1 error covariance matrix was allowed to vary across participants. The results from the analyses of five published studies showed that when the Level-1 error covariance matrix was allowed to vary across participants, some relatively large differences in autocorrelation estimates and error variance estimates emerged. The changes in modeling the variance structure did not change the conclusions about which fixed effects were statistically significant in most of the studies, but there was one exception. The fit indices did not consistently support selecting either the more complex covariance structure, which allowed the covariance parameters to vary across participants, or the simpler covariance structure. Given the uncertainty in model specification that may arise when modeling single-case data, researchers should consider conducting sensitivity analyses to examine the degree to which their conclusions are sensitive to modeling choices.