A Bayesian Approach to More Stable Estimates of Group-Level Effects in Contextual Studies

Multilevel analyses are often used to estimate the effects of group-level constructs. However, when using aggregated individual data (e.g., student ratings) to assess a group-level construct (e.g., classroom climate), the observed group mean might not provide a reliable measure of the unobserved latent group mean. In the present article, we propose a Bayesian approach that can be used to estimate a multilevel latent covariate model, which corrects for the unreliable assessment of the latent group mean when estimating the group-level effect. A simulation study was conducted to evaluate the choice of different priors for the group-level variance of the predictor variable and to compare the Bayesian approach with the maximum likelihood approach implemented in the software Mplus. Results showed that, under problematic conditions (i.e., small number of groups, predictor variable with a small ICC), the Bayesian approach produced more accurate estimates of the group-level effect than the maximum likelihood approach did.     

Probabilistic choice (models) as a result of balancing multiple goals

We conceptualize probabilistic choice as the result of the simultaneous pursuit of multiple goals in a vector optimization representation, which is reduced to a scalar optimization that implies goal balancing. The majority of prior theoretical and empirical work on such probabilistic choice is based on random utility models, the most basic of which assume that each choice option has a valuation that has a deterministic (systematic) component plus a random component determined by some specified distribution. An alternate approach to probabilistic choice has considered maximization of one quantity (e.g., utility), subject to constraints on one or more other quantities (e.g., cost). The multiple goal perspective integrates the results regarding the well-studied multinomial logit model of probabilistic choice that has been derived from each of the above approaches; extends the results to other models in the generalized extreme value (GEV) class; and relates them to recent axiomatic work on the utility of gambling.     

Using Community Surveys to Inform the Planning and Implementation of Environmental Change Strategies: Participatory Research in 12 Washington Communities

A number of studies have demonstrated the efficacy of environmental change strategies (ECS) in effecting community-level change on attitudes and behaviors related to underage drinking (Treno and Lee in Alcohol Res Health 26:35–40, 2002; Birckmayer et al. in J Drug Educ 34(2):121–153, 2004). Primary data collection to inform the design of these strategies, however, can be resource intensive and exceed the capacity of community stakeholders. This study describes the participatory planning and implementation of community-level surveys in 12 diverse communities in the state of Washington. These surveys were conducted through collaborations among community volunteers and evaluation experts assigned to each community. The surveys were driven by communities’ prevention planning needs and interests; constructed from collections of existing, field-tested items and scales; implemented by community members; analyzed by evaluation staff; and used in the design of ECS by community-level leaders and prevention practitioners. The communities varied in the content of their surveys, in their sampling approaches and in their data collection methods. Although these surveys were not conducted using traditional rigorous population survey methodology, they were done within limited resources, and the participatory nature of these activities strengthened the communities’ commitment to using their results in the planning of their environmental change strategies.     

Correlated change of Big Five personality traits across the lifespan: A search for determinants

Correlated change between different personality traits has recently caught the attention of researchers studying personality development. We conducted two studies to examine age effects (Study 1) and effects of cognitive ability (Study 2) on this phenomenon. Results indicated that correlated change was relatively stable from adolescence through adulthood, and then increased after age 70. Second, correlated change was greater among traits that have been linked to the same developmental processes (e.g., social investment or maturation of specific neurological systems). Third, cognitive ability was negatively associated with correlated change. Collectively, our findings suggest that personality change is partly driven by broad mechanisms affecting multiple traits. Associations with age and cognitive ability provide important leads regarding the possible nature of these mechanisms.     

Gender differences in the mean level,variability, and profile shape of student achievement: Results from 41 countries

A domain-specific hierarchical conceptualization of mathematics achievement can be represented by the standard psychometric model in which a single latent dimension accounts for observed individual differences in scores on the respective subdomains (e.g., quantity). Alternatively, a fully hierarchical conceptualization of achievement can be represented by a nested-factor model in which individual differences in subdomain-specific scores are explained by both general student achievement and specific mathematics achievement. The authors applied both models to study the gender similarity hypothesis, the greater male variability hypothesis, and the masking hypothesis, which predicts that gender differences in general student achievement mask gender differences in both the means and the variability of specific mathematics achievement. Representative data were obtained from 275,369 15-year-old students in 41 countries. The results supported these hypotheses in most countries, demonstrating that a fully hierarchical conceptualization of achievement in terms of the nested-factor model significantly contributes to a better understanding of gender differences in the mean level, variability, and shape of students' achievement profiles.     

Is the Flynn effect on g?: A meta-analysis

Black/White differences in mean IQ have been clearly shown to strongly correlate with g loadings, so large group differences on subtests of high cognitive complexity and small group differences on subtests of low cognitive complexity. IQ scores have been increasing over the last half century, a phenomenon known as the Flynn effect. Flynn effect gains are predominantly driven by environmental factors. Might these factors also be responsible for group differences in intelligence? The empirical studies on whether the pattern of Flynn effect gains is the same as the pattern of group differences yield conflicting findings. A psychometric meta-analysis on all studies with seven or more subtests reporting correlations between g loadings and standardized score gains was carried out, based on 5 papers, yielding 11 data points (total N = 16,663). It yielded a true correlation of − .38, and none of the variance between the studies could be attributed to moderators. It appears that the Flynn effect and group differences have different causes. Suggestions for future research are discussed.     

Perceptual Learning in the Rat: Stimulus Differentiation or Latent Inhibition of Common Elements?

Preexposure to an unreinforced stimulus facilitates learning (perceptual learning) under some conditions, but it can have the opposite effect (latent inhibition) under other conditions. Researchers have suggested that perceptual learning depends on a change of context, whereas latent inhibition is usually context specific. The associative theory explains both phenomena within a single framework. The authors report 4 experiments that show that perceptual learning does not depend on a context change. The experiments suggest that latent inhibition, unlike perceptual learning, depends on passive exposure. Thus the results do not support the associative theory. They are more consistent with Gibson's stimulus-differentiation theory.     

Traumatic Attachments and Self-Harm Behaviors

Abstract

Work and the structure it affords is one of the most important vehicles for the expression of worth in our society. With so much invested in the external world of position and achievement, threats to job security pose fundamental challenges to individual identity. Recent upheavals in the workplacedownsizings, early retirements, and corporate reorganizationshave shaken the psychological equilibrium of many of our clients, giving rise to feelings of despair and hopelessness. When disruptive and unwanted changes occur later in life, they become additionally tinged with latent concerns about aging and finding meaning as a mature adult.     

Assessing the Relationship Between Differentiation and Infidelity

SUMMARY

Differentiation and infidelity have been theoretically related. However, few studies have tested whether the concepts in differentiation are statistically related to infidelity. One hundred nineteen participants in the present study completed two inventories assessing their level of differentiation and engaging in infidelity. Two-step structural equation modeling is used to determine the degree to which differentiation relates to infidelity. Results indicated that, though differentiation may be part of a plausible model of infidelity behavior, there are potentially other models that may be relevant in engaging in infidelity. The findings and implications are discussed.