Elder abuse and neglect among veterans in Greater Los Angeles: prevalence, types, and intervention outcomes

This study examined the prevalence, types, and intervention outcomes of elder abuse/neglect among a veteran population. A review of medical records of 575 veterans who had received services from the Veteran's Affairs Geriatric Outpatient Clinic in Los Angeles during a three-year period found 31 veterans (5.4%) who had an elder abuse report filed on their behalf. Prevalence of elder abuse/neglect was higher among older (80+) and Caucasian and African American veterans. Eight of 31 victims suffered from more than one type of elder abuse including self-neglect. Financial abuse and self-neglect were the most commonly reported types. Family members were perpetrators in the majority of the cases, excluding self-neglect. However, three-quarters of financial abuse cases were committed by non-family members. Almost one-half of the victims had dementia and eight were clinically depressed. The most common intervention was to move victims from their unsafe home into a nursing home or board and care facility, followed by conservatorship arrangement. These interventions were most frequently used for victims with dementia, and conservatorship was often arranged with another type of intervention, such as a move to a nursing home. Victims who remained at home received conservatorship or outside supportive services or a combination of both. This study calls for more comprehensive and systematic research on elder abuse/neglect at multi-settings in order to generate useful information for prevention and detection of, and effective intervention in elder abuse and neglect in the veteran population.     

Bayesian and Frequentist Inference in Partially Identified Models

A large‐sample approximation of the posterior distribution of partially identified structural parameters is derived for models that can be indexed by an identifiable finite‐dimensional reduced‐form parameter vector. It is used to analyze the differences between Bayesian credible sets and frequentist confidence sets. We define a plug‐in estimator of the identified set and show that asymptotically Bayesian highest‐posterior‐density sets exclude parts of the estimated identified set, whereas it is well known that frequentist confidence sets extend beyond the boundaries of the estimated identified set. We recommend reporting estimates of the identified set and information about the conditional prior along with Bayesian credible sets. A numerical illustration for a two‐player entry game is provided.     

Social Activity, School-Related Activity, and Anti-Substance Use Media Messages on Adolescent Tobacco and Alcohol Use

In this article, we present the effects of three hypothesized protective factors: social activities, school-related activities, and anti-substance use media messages on adolescent tobacco and alcohol use. Data were drawn from the "Monitoring the Future" (MTF) research project, which was conducted by the Institute for Social Research at the University of Michigan. The sample included 2,551 twelfth-grade students. The results of the structural equation model showed that exposure to media anti-drug messages had an indirect negative effect on tobacco and alcohol use through school-related activity and social activity. The results suggest that comprehensive ecological interventions encompassing media, family, and school can increase on the preventive effects of adolescent's substance use.     

Physical and Psycho-Social Predictors of Adolescents’ Suicide Behaviors

The current study examined the relationship between suicidal behaviors and physical and psycho-social predictors including body image, weight control behaviors, and risky sexual behaviors among Asian, African American, Caucasian, and Hispanic adolescents. This study used the 2007 Youth Risk Behavior Survey (YRBS). The target populations were 11,134 adolescents (5,636 female and 5,498 male) in 9th–12th grade who completed the survey. A linear regression was conducted to examine the correlation between predictors and suicidal behaviors. The results showed that gender, grade, depression, substance use, body image, weight control behaviors, and risky sexual behaviors were significant predictors of adolescents’ suicidal behaviors, while race/ethnicity was not a good predictor. Also, there were significant gender and grade differences in suicidal behaviors. Based on the results, practice implications for suicide prevention were discussed.     

Mainstream and Ethnic Volunteering by Korean Immigrants in the United States

Asian immigrants accounted for one-eighth of the total U.S. population in 2009. With Asian immigrants having higher levels of education and income than average Americans, their potential contribution to American philanthropy will be even more significant. This study examines the volunteering patterns of Korean immigrants, one of the fastest growing segments of the Asian immigrant population in the United States. This study explains Korean immigrants’ volunteering within ethnic and mainstream (American) organizations using the concepts of bonding and bridging social capital. The bivariate probit regression results suggest that ethnic volunteering and mainstream volunteering are generally the substitutes for each other. The findings nevertheless suggest that providing Asian immigrants’ with English education and continuing education opportunities may boost their volunteering to mainstream nonprofit organizations without discouraging their volunteering for ethnic organizations.     

简约的白色世界

<正>你有没有想象过住在一座这样的房子里:拥有完美的极简设计与令人惊叹的洁净,在原木打造的白色通透空间中,一切似乎都轻盈地悬浮着。沙发、茶几、床具,甚至橱柜,几乎所有的家具都是纯白色,人在其中,彷佛置身于一个童话般的白色世界。     

Efficient Estimation of the Seemingly Unrelated Regression Cointegration Model and Testing for Purchasing Power Parity

This paper studies the efficient estimation of seemingly unrelated linear models with integrated regressors and stationary errors. We consider two cases. The first one has no common regressor among the equations. In this case, we show that by adding leads and lags of the first differences of the regressors and estimating this augmented dynamic regression model by generalized least squares using the long-run covariance matrix, we obtain an efficient estimator of the cointegrating vector that has a limiting mixed normal distribution. In the second case we consider, there is a common regressor to all equations, and we discuss efficient minimum distance estimation in this context. Simulation results suggests that our new estimator compares favorably with others already proposed in the literature. We apply these new estimators to the testing of the proportionality and symmetry conditions implied by purchasing power parity (PPP) among the G-7 countries. The tests based on the efficient estimates easily reject the joint hypotheses of proportionality and symmetry for all countries with either the United States or Germany as numeraire. Based on individual tests, our results suggest that Canada and Germany are the most likely countries for which the proportionality condition holds, and that Italy and Japan for the symmetry condition relative to the United States.     

Model Averaging Using the Kullback Information Criterion in Estimating Effective Doses for Microbial Infection and Illness

Since the National Food Safety Initiative of 1997, risk assessment has been an important issue in food safety areas. Microbial risk assessment is a systematic process for describing and quantifying a potential to cause adverse health effects associated with exposure to microorganisms. Various dose-response models for estimating microbial risks have been investigated. We have considered four two-parameter models and four three-parameter models in order to evaluate variability among the models for microbial risk assessment using infectivity and illness data from studies with human volunteers exposed to a variety of microbial pathogens. Model variability is measured in terms of estimated ED01s and ED10s, with the view that these effective dose levels correspond to the lower and upper limits of the 1% to 10% risk range generally recommended for establishing benchmark doses in risk assessment. Parameters of the statistical models are estimated using the maximum likelihood method. In this article a weighted average of effective dose estimates from eight two- and three-parameter dose-response models, with weights determined by the Kullback information criterion, is proposed to address model uncertainties in microbial risk assessment. The proposed procedures for incorporating model uncertainties and making inferences are illustrated with human infection/illness dose-response data sets.     

Visualization of multidimensional data using modifications of the Grand Tour

Current implementations of Asimov's Grand Tour (for example in XLISP-STAT by Tierney, 1990, or in XGobi by Buja et al., 1996) do not remember the path of projections and show only the current state during the touring process. We propose a modification of the Grand Tour, named Tracking Grand Tour (TGT), that shows the trace of the touring process as small 'comet trails' of the projected points. The usefulness of the TGT is demonstrated with a simulated and a real data set.