The potential for international and transnational public service advertising in public spaces in American and Chinese global cities: Conclusions from a 2010 survey of advertisements in subways in Beijing,New York,Shanghai and Washington,DC

Can we construct transnational or international public service advertising to counterbalance the proliferation of transnational commercial advertising? As an important first step in exploring the possibility of such an application of shared media public diplomacy among nations, this paper describes a complete survey of commercial and public service advertisements collected from the public spaces of subway systems in American and Chinese cities in 2010 – New York, Washington, DC, Shanghai and Beijing – to reveal the range of themes of commercial and public service ads in these spaces. The study reveals first that analogous commercial and public service ads are ubiquitous in the public spaces of both Chinese and American cities. Second, many of the themes that might appear in international or transnational public service ads are already being portrayed in ads created by local or national governments or NGOs, although these themes are portrayed in ads created by different sets of actors in China and in the US: government actors and a few international NGOs in Chinese cities, and governments, corporations and non-profit organizations in the case of American cities. Finally, the survey reveals that in all four cities there are many commercial advertisements that appeal to the identity of a transnational consumer, but that there are almost no public service ads that appeal to the identity of a transnational citizen: merely local or national ones who can solve such public problems as global warming, education, and health issues.     

Exploring the relationship between experiential avoidance, alcohol use disorders, and alcohol-related problems among first-year college students

Abstract Objective: This study explored the relationship of experiential avoidance (eg, the tendency to avoid, suppress, or otherwise control internal experiences even when doing so causes behavioral harm) to alcohol use disorders and alcohol-related problems. Participants: Cross-sectional data were collected from 240 undergraduate college students in their first year in college between December 2009 and April 2010. Methods: Participants completed a diagnostic interview and online self-report survey. Results: Students with a history of alcohol abuse or dependence had significantly higher levels of experiential avoidance relative to students with no alcohol use disorder diagnosis. A hierarchical linear regression analysis found that experiential avoidance significantly predicted alcohol-related problems, even after controlling for gender and psychological distress. Furthermore, experiential avoidance mediated the relationship of psychological distress to alcohol-related problems. Conclusions: These findings suggest that experiential avoidance may play a role in problematic alcohol use among college students.     

Child-Focused Family Therapy: Behavioural Family Therapy Versus Brief Family Therapy

We examined the effectiveness of behavioural family therapy (following the treatment agenda outlined in Fleischman, Horne and Arthur, 1983) and brief family therapy (following the procedures outlined in Fisch, Weakland and Segal, 1985), in the treatment of child psychological disorders. The parents of the 49 children referred to the outpatient unit of a children's hospital completed the Child Behavior Checklist (CBCL) (Achenbach and Edelbrock, 1983). Three scales of the CBCL were examined to assess the effectiveness of the two therapeutic approaches pre- to post-treatment. Significant pre- and post-treatment differences were found for behavioural family therapy on the Internalizing, Externalizing, and Sum T scales and for brief family therapy on the Internalizing and Sum T scales. Sum T scales represent the sum of scores across all sub-scales of the CBCL. Neither treatment was found to be more effective than the other.     

Bayesian variable selection for proportional hazards models

The authors consider the problem of Bayesian variable selection for proportional hazards regression models with right censored data. They propose a semi-parametric approach in which a nonparametric prior is specified for the baseline hazard rate and a fully parametric prior is specified for the regression coefficients. For the baseline hazard, they use a discrete gamma process prior, and for the regression coefficients and the model space, they propose a semi-automatic parametric informative prior specification that focuses on the observables rather than the parameters. To implement the methodology, they propose a Markov chain Monte Carlo method to compute the posterior model probabilities. Examples using simulated and real data are given to demonstrate the methodology.     

Civilizing Northumberland: Representations of Englishness in the Tudor State

Taking Northumberland as a case study, this paper explores the wider implications of the Tudor strategy of reform by centralization, uniformity, and cultural imperialism. It reappraises the notion that the growth of centralized government at the expense of regional magnates was unambiguously a form of modernization; and argues that the essential character of the Tudor state and the radical nature of Tudor reform have been obscured by the historians' practice of viewing developments in terms of the rise of the nation.     

The Effect of School Choice on Participants: Evidence from Randomized Lotteries

School choice has become an increasingly prominent strategy for enhancing academic achievement. To evaluate the impact on participants, we exploit randomized lotteries that determine high school admission in the Chicago Public Schools. Compared to those students who lose lotteries, students who win attend high schools that are better in a number of dimensions, including peer achievement and attainment levels. Nonetheless, we find little evidence that winning a lottery provides any systematic benefit across a wide variety of traditional academic measures. Lottery winners do, however, experience improvements on a subset of nontraditional outcome measures, such as self‐reported disciplinary incidents and arrest rates.     

Issues with using baseline in last observation carried forward analysis

The topic of this paper was prompted by a study for which one of us was the statistician. It was submitted to Annals of Internal Medicine. The paper had positive reviewer comment; however, the statistical reviewer stated that for the analysis to be acceptable for publication, the missing data had to be accounted for in the analysis through the use of baseline in a last observation carried forward imputation. We discuss the issues associated with this form of imputation and recommend that it should not be undertaken as a primary analysis.     

Influence Function Based Variance Estimation and Missing Data Issues in Case-Cohort Studies

Recognizing that the efficiency in relative risk estimation for the Cox proportional hazards model is largely constrained by the total number of cases, Prentice (1986) proposed the case-cohort design in which covariates are measured on all cases and on a random sample of the cohort. Subsequent to Prentice, other methods of estimation and sampling have been proposed for these designs. We formalize an approach to variance estimation suggested by Barlow (1994), and derive a robust variance estimator based on the influence function. We consider the applicability of the variance estimator to all the proposed case-cohort estimators, and derive the influence function when known sampling probabilities in the estimators are replaced by observed sampling fractions. We discuss the modifications required when cases are missing covariate information. The missingness may occur by chance, and be completely at random; or may occur as part of the sampling design, and depend upon other observed covariates. We provide an adaptation of S-plus code that allows estimating influence function variances in the presence of such missing covariates. Using examples from our current case-cohort studies on esophageal and gastric cancer, we illustrate how our results our useful in solving design and analytic issues that arise in practice.     

Bootstrap goodness-of-fit test for the beta-binomial model

A common question in the analysis of binary data is how to deal with overdispersion. One widely advocated sampling distribution for overdispersed binary data is the beta-binomial model. For example, this distribution is often used to model litter effects in toxicological experiments. Testing the null hypothesis of a beta-binomial distribution against all other distributions is difficult, however, when the litter sizes vary greatly. Herein, we propose a test statistic based on combining Pearson statistics from individual litter sizes, and estimate the p-value using bootstrap techniques. A Monte Carlo study confirms the accuracy and power of the test against a beta-binomial distribution contaminated with a few outliers. The method is applied to data from environmental toxicity studies.