Implicit and Self-Attributed Dependency Needs in Homeless Men and Women

Recent metaanalyses indicate that women consistently obtain higher scores than men do on self-report dependency measures, but not on projective dependency tests (R. F. Bornstein, 1995, 1996). To explore this issue in a heretofore unexamined population, we analyzed archival data from 85 homeless participants (40 women and 45 men) enrolled in a vocational rehabilitation program, using the MMPI Dependency (Dy) Scale (L. Navran, 1954) and the Rorschach Oral Dependency (ROD) Scale (J. M. Masling, L. Rabie, & S. H. Blondheim, 1967). Consistent with earlier results, there were no gender differences in projective dependency scores, but contrary to earlier results, there were also no gender differences in self-reports of dependency. These findings suggest that stressful conditions like homelessness may mitigate the impact of gender on self-reported dependency.     

Non-conjugate prior distribution assessment for multivariate normal sampling

Elicitation methods are proposed for quantifying expert opinion about a multivariate normal sampling model. The natural conjugate prior family imposes a relationship between the mean vector and the covariance matrix that can portray an expert's opinion poorly. Instead we assume that opinions about the mean and the covariance are independent and suggest innovative forms of question which enable the expert to quantify separately his or her opinion about each of these parameters. Prior opinion about the mean vector is modelled by a multivariate normal distribution and about the covariance matrix by both an inverse Wishart distribution and a generalized inverse-Wishart (GIW) distribution. To construct the latter, results are developed that give insight into the GIW parameters and their interrelationships. Certain of the elicitation methods exploit unconditional assessments as fully as possible, since these can reflect an expert's beliefs more accurately than conditional assessments. Methods are illustrated through an example.     

When Prejudice Is Popular: Implications for Discriminatory Behavior

Prejudice and popularity represent two major areas of research. Yet studies have not considered whether prejudiced adolescents actually can be popular. Among 572 high school students (M_age = 15.80 years), the current study tested the association between popularity (based on sociometric peer nominations) and sexual prejudice against gay and lesbian individuals, moderated by gender and perspective taking. As hypothesized, the association was significant for males but not females, and it was significant for adolescents lower on perspective taking but not those higher on perspective taking. Moreover, adolescents who were popular and expressed strong sexual prejudice were more likely to engage in homophobic behavior than prejudiced adolescents who were less popular. Popular adolescents with strong sexual prejudice beliefs may be more prone to use homophobic behavior as a way to maintain their dominant position. Similarly, prejudiced adolescents who are popular may face less pushback for their engagement in homophobic behavior. Continued attention to the connection between sexual prejudice and popularity is important because of the high status, influence, and visibility of popular adolescents.     

Educational imposters and fake degrees

We develop a sociological context for understanding the phenomenon of falsely claimed educational credentials and analyze national data that cast light on the incidence of false degrees. We find that about 6% of Bachelor's degrees and 35% of Associate's degrees are falsely claimed. Most individuals who falsely claim degrees have attended the college in question. Many have nearly completed the required credits, but claim a degree without having finished. The socio-demographic profile of persons falsely claiming credentials is consistent with Merton's theory of innovative deviance, but not with the theory of status inconsistency.     

Evaluating the impact of conditional cash transfer programs on fertility: the case of the Red de Protección Social in Nicaragua

Evaluating the impact of poverty-reduction programs on fertility is complicated given that changes in incentives to have children take time to be incorporated into decision making and evaluation periods are usually quite brief. We explore the use of birth spacing as a short-run indicator of the impact of poverty-reduction programs on fertility. The data come from a Nicaraguan conditional cash transfer program that offers incentives for poor households to invest in children’s health, nutrition, and education. We estimate a stratified Cox proportional hazard model and find that the program decreased the hazard of a birth, indicating an increase in birth spacing.     

Abusive supervision and the entitled employee

We present two studies that examine the effects of psychological entitlement on employees' ratings of abusive supervision and their behavioral reactions to these perceptions. Study 1 indicated that entitlement was positively associated with ratings of abusive supervision. Perceived abuse was, in turn, associated with upward undermining behaviors and organizational deviance. In Study 2, we re-examined the hypothesized relationships using paired data from employees and their coworkers. The results replicated those from the first study and showed that entitled employees rated supervisors as more abusive than coworkers who shared the same supervisors. Although this variance is likely driven by a combination of perceptual distortion and actual abusive behaviors, the ultimate implication is that psychologically entitled employees are prone to feel that they are victims of abuse and to react in undesirable ways.     

The Bayesian and frequentist approaches to testing a one-sided hypothesis about a multivariate mean

This paper compares the Bayesian and frequentist approaches to testing a one-sided hypothesis about a multivariate mean. First, this paper proposes a simple way to assign a Bayesian posterior probability to one-sided hypotheses about a multivariate mean. The approach is to use (almost) the exact posterior probability under the assumption that the data has multivariate normal distribution, under either a conjugate prior in large samples or under a vague Jeffreys prior. This is also approximately the Bayesian posterior probability of the hypothesis based on a suitably flat Dirichlet process prior over an unknown distribution generating the data. Then, the Bayesian approach and a frequentist approach to testing the one-sided hypothesis are compared, with results that show a major difference between Bayesian reasoning and frequentist reasoning. The Bayesian posterior probability can be substantially smaller than the frequentist p-value. A class of example is given where the Bayesian posterior probability is basically 0, while the frequentist p-value is basically 1. The Bayesian posterior probability in these examples seems to be more reasonable. Other drawbacks of the frequentist p-value as a measure of whether the one-sided hypothesis is true are also discussed.     

Extending mixtures of multivariate <Emphasis Type="Italic">t</Emphasis>-factor analyzers

Model-based clustering typically involves the development of a family of mixture models and the imposition of these models upon data. The best member of the family is then chosen using some criterion and the associated parameter estimates lead to predicted group memberships, or clusterings. This paper describes the extension of the mixtures of multivariate t-factor analyzers model to include constraints on the degrees of freedom, the factor loadings, and the error variance matrices. The result is a family of six mixture models, including parsimonious models. Parameter estimates for this family of models are derived using an alternating expectation-conditional maximization algorithm and convergence is determined based on Aitken’s acceleration. Model selection is carried out using the Bayesian information criterion (BIC) and the integrated completed likelihood (ICL). This novel family of mixture models is then applied to simulated and real data where clustering performance meets or exceeds that of established model-based clustering methods. The simulation studies include a comparison of the BIC and the ICL as model selection techniques for this novel family of models. Application to simulated data with larger dimensionality is also explored.     

Naming,blaming and claiming ablism: the lived experiences of lawyers and advocates with disabilities

The social model explains that different abilities are not the true cause of disablement. Ablist institutions and practices construct a certain level of ability as disability. How do people respond when they are being disabled by society? This study analyses how 28 advocates and lawyers with disabilities respond when they confront ablism. This study employs the naming, blaming and claiming model to map the conduct of 28 lawyers and advocates with disabilities from Australia, the United Kingdom and the United States. Despite their empowered position, participants often did not claim for every act of ablism. This study analyses why participants did not claim. One of the primary issues raised by participants was a gap between the range of parties who caused disablement in society and the way in which anti-discrimination laws attributed duties.