Distractor effect on the latent inhibition of conditioned flavor aversion in rats

Using a conditioned flavor aversion procedure with rats as subjects, the effect of the addition of a distractor stimulus on the magnitude of the latent inhibition effect was examined. Experiment 1 showed that latent inhibition to vinegar was attenuated by the addition of sucrose during preexposure. On the other hand, sucrose added during conditioning to vinegar did not attenuate latent inhibition. It was also found that the degree of latent inhibition to the vinegar-sucrose compound solution was less when vinegar alone was preexposed (i.e., when sucrose was added only during conditioning) than when the compound solution was preexposed (i.e., when sucrose was added both during preexposure and during conditioning). Experiment 2 gave similar results but with sucrose assigned as the target flavor and vinegar as the distractor. These findings are in full agreement with the generalization decrement account of latent inhibition.     

Bayesian estimation and testing of structural equation models

The Gibbs sampler can be used to obtain samples of arbitrary size from the posterior distribution over the parameters of a structural equation model (SEM) given covariance data and a prior distribution over the parameters. Point estimates, standard deviations and interval estimates for the parameters can be computed from these samples. If the prior distribution over the parameters is uninformative, the posterior is proportional to the likelihood, and asymptotically the inferences based on the Gibbs sample are the same as those based on the maximum likelihood solution, for example, output from LISREL or EQS. In small samples, however, the likelihood surface is not Gaussian and in some cases contains local maxima. Nevertheless, the Gibbs sample comes from the correct posterior distribution over the parameters regardless of the sample size and the shape of the likelihood surface. With an informative prior distribution over the parameters, the posterior can be used to make inferences about the parameters underidentified models, as we illustrate on a simple errors-in-variables model.We thank David Spiegelhalter for suggesting applying the Gibbs sampler to structural equation models to the first author at a 1994 workshop in Wiesbaden. We thank Ulf Böckenholt, Chris Meek, Marijtje van Duijn, Clark Glymour, Ivo Molenaar, Steve Klepper, Thomas Richardson, Teddy Seidenfeld, and Tom Snijders for helpful discussions, mathematical advice, and critiques of earlier drafts of this paper.     

Subtypes of severe psychological distress among US Air Force remote warriors: A latent class analysis

US Air Force remote warrior personnel include a range of military personnel composed of remotely piloted aircraft aircrew, intelligence operators, and cyber warfare operators. Job duties in these professions entail long work hours, rotating shifts, and regular engagement in combat operations. Although research has identified a number of factors correlated with elevated burnout and emotional distress in this population, little is known about the unique needs of discrete subgroups of distressed personnel. In a sample of 7,550 US Air Force remote warriors, results of latent class analysis yielded four distinct classes. Three of the four reported moderately elevated burnout and job dissatisfaction but differed with respect to demographics and development career stage. The fourth group reported significantly higher levels of emotional distress, burnout, job dissatisfaction, and problems in living. This latter group was comparable to the mid-career group with respect to demographics, although this group had much lower levels of responsibility and indicators of career advancement. Results suggest that, among remote warrior personnel, there are several subtypes of elevated emotional distress. Prevention and intervention strategies that are matched to each subtype may yield better occupational and mental health outcomes than universal, “one size fits all” strategies.     

Predicting elections from the most important issue: A test of the take‐the‐best heuristic

We used the take‐the‐best heuristic to develop a model to forecast the popular two‐party vote shares in U.S. presidential elections. The model draws upon information about how voters expect the candidates to deal with the most important issue facing the country. We used cross‐validation to calculate a total of 1000 out‐of‐sample forecasts, one for each of the last 100 days of the ten U.S. presidential elections from 1972 to 2008. Ninety‐seven per cent of forecasts correctly predicted the winner of the popular vote. The model forecasts were competitive compared to forecasts from methods that incorporate substantially more information (e.g., econometric models and the Iowa Electronic Markets). The purpose of the model is to provide fast advice on which issues candidates should stress in their campaign. Copyright © 2010 John Wiley & Sons, Ltd.     

Chinese college students' general and relationship‐specific representations of adult attachment: Variable‐centred and person‐centred analysis

Formerly, researchers often treated adult attachment as a trait‐like construct with consistency across relationship contexts. However, recent studies have shown that people possess multiple relationship‐specific attachment representations, and inter‐correlations among them are only in a small‐to‐medium range. The aim of this study is to test whether these variable‐centred results could be replicated in China and further supplement them with a person‐centred analysis focusing on identifying prototypical patterns of multiple working models across relationships. We administrated measurements of general and four relationship‐specific (mother/father/best friend/romantic partner) working models and indicators of psychological adjustment upon 302 Chinese college students. Results from variable‐centred analysis demonstrated the cross‐relationship variability in working models. Furthermore, global indicators of psychological adjustment were better predicted by general models, while relationship‐specific indicators were better predicted by corresponding relationship‐specific models. These results largely replicate previous Western studies, supporting the existence of multiple attachment representations in China. In person‐centred analysis, a latent profile analysis identified four typical classes of working model profiles: all‐average, all‐secure, romantic‐insecure and peer‐secure. These classes differed not only in the cross‐relationship variability of their working models, but also in their levels of psychological adjustment. These interesting patterns may have theoretical implications and are worthy of further examination.     

Multicultural Personality Dispositions and Trait Emotional Intelligence: An Exploratory Study

ABSTRACT

This study examined the relationship between multicultural personality dispositions and trait emotional intelligence. The sample included 152 graduate education students enrolled at a university in a large northeastern city of the United States. The multicultural personality dispositions of Cultural Empathy and Social Initiative predicted variance in trait emotional intelligence above and beyond the variance accounted for by gender and potential socially desirable responding. Study limitations are highlighted, and suggestions for follow-up quantitative and qualitative research are presented.     

Understanding memory impairment with memory models and hierarchical Bayesian analysis

The study of human episodic memory is a topic that interests cognitive and mathematical psychologists as well as clinicians interested in the diagnosis and assessment of Alzheimer’s disease and related disorders (ADRD). In this paper, we use simple cognitive models for the recognition and recall tasks typically applied in clinical assessments of ADRD to study memory performance in ADRD patients. Our models make use of hierarchical Bayesian methods as a way to model individual differences in patient performance and to facilitate the modeling of performance changes that occur during multiple recall tasks. We show how the models are able to account for different aspects of patient performance, and also discuss some of the predictive capabilities of the model. We conclude with a discussion on the scope to improve on our results by discussing the link between memory theory in psychology and clinical practice.     

The three latent classes of adolescent delinquency and the risk factors for membership in each class

This study used latent class analysis to examine subpopulation membership based on self-reports of delinquent behaviors obtained from Australian youth. Three discrete identifiable classes were derived based on 51 indicators of physical violence, property damage, minor infractions, drug use, and social delinquency. One class of youth engaged in primarily rule breaking and norm violations including underage alcohol use, typical of this age period. A second class was more actively delinquent emphasizing drug use, trespassing, and various forms of disobedience. A third class of highly delinquent youth differed from their counterparts by endorsing drug use, thievery that involved stealing money, goods, and cars, property damage, gambling, precocious sexual experiences, involvement with pornographic materials, and fighting. Multinomial logistic regression predicting class membership indicated highly delinquent youth were more likely to be older males, use venting coping strategies, and be fun or novelty seeking compared with rule breakers. Findings are discussed in terms of refining current taxonomic arguments regarding the structure of delinquency and implications for prevention of early-stage antisocial behavior.     

Sex differences in latent cognitive abilities ages 5 to 17: Evidence from the Differential Ability Scales—Second Edition

Sex differences in the latent general and broad cognitive abilities underlying the Differential Ability Scales, Second Edition were investigated for children and youth ages 5 through 17. Multi-group mean and covariance structural equation modeling was used to investigate sex differences in latent cognitive abilities as well as changes in these differences across age. Most broad abilities showed mean differences across the sexes, and all such differences varied across ages. Girls showed an advantage on the processing speed (Gs) first-order residual factor. Girls also showed advantages at some ages on free-recall memory, a narrow ability of long term retrieval (Glr). Boys showed a developmentally-related advantage on a visual-spatial ability (Gv) first-order residual factor, depending on age. Younger girls showed an advantage on short-term memory (Gsm). No statistically significant sex differences were shown on the latent comprehension-knowledge (Gc) factor, or on a second-order, latent g factor. Boys showed larger variances for several broad abilities, some substantial, but those differences were not statistically significant.