Climate Hazards and Risk Status: Explaining Climate Risk Assessment,Behavior, and Policy Support

Based on a national survey conducted two years after Hurricanes Katrina and Rita hit the U.S. Gulf Coast, we investigate the ways in which major “risk conditions,” which may subject individuals to climate-related hazards, translate to varying responses to risk: including risk assessment, behavioral modification, and policy support. We present a model that an individual's risk status can be determined by their embeddedness in risk conditions, which include both exposure to risk sources and access to risk information. Our findings suggest that an individual's access to information on climate risks significantly influences their proactive responses to climate hazards, as in, those who have objective knowledge of climate risks and social ties with concerned others are more likely to be proactive toward climate risks. It is also observed that an individual's political views tend to predispose their assessment of climate risks, which further affect their behavioral and policy responses.     

Obesity and Food Choices Among Faculty and Staff at a Large Urban University

Abstract

Objective: In order to address increasing health care costs associated with obesity, this study sought to determine prevalence of overweight and obesity and examine eating behaviors, food choices, health beliefs, and attitudes of university employees. Participants and Methods: An online survey was distributed to > 3,800 faculty and staff at a large public metropolitan university in Winter 2008. Results: Almost half (48%) of 806 respondents were classified as overweight or obese. Compared to those with normal weights, overweight and obese respondents consumed fewer fruits and vegetables (p < .05), were less confident in making healthful food choices (p < .001), and were more influenced by food choices available in on-campus dining facilities (p < .05). Conclusions: Obesity among university employees warrants attention. Because these employees have less self-efficacy and consume less healthful diets than their normal weight colleagues, universities need to improve on-campus access to healthful foods.     

Model selection for mixture‐based clustering for ordinal data

One of the key questions in the use of mixture models concerns the choice of the number of components most suitable for a given data set. In this paper we investigate answers to this problem in the context of likelihood‐based clustering of the rows of a matrix of ordinal data modelled by the ordered stereotype model. Two methodologies for selecting the best model are demonstrated and compared. The first approach fits a separate model to the data for each possible number of clusters, and then uses an information criterion to select the best model. The second approach uses a Bayesian construction in which the parameters and the number of clusters are estimated simultaneously from their joint posterior distribution. Simulation studies are presented which include a variety of scenarios in order to test the reliability of both approaches. Finally, the results of the application of model selection to two real data sets are shown.     

Generalized order statistic processes and Pfeifer records

We introduce a uniform generalized order statistic process. It is a simple Markov process whose initial segment can be identified with a set of uniform generalized order statistics. A standard marginal transformation leads to a generalized order statistic process related to non-uniform generalized order statistics. It is then demonstrated that the nth variable in such a process has the same distribution as an nth Pfeifer record value. This process representation of Pfeifer records facilitates discussion of the possible limit laws for Pfeifer records and, in some cases, of sums thereof. Because of the close relationship between Pfeifer records and generalized order statistics, the results shed some light on the problem of determining the nature of the possible limiting distributions of the largest generalized order statistic.     

Parental military service and adolescent well‐being: mental health,social connections and coping among youth in the USA

The association between parental military work factors and adolescent's well‐being was examined. Data were collected from 1036 military youth. Using a within‐group design, we examined adolescent's well‐being related to parental absence, school and neighbourhood transitions, paygrade/rank and participation in military‐sponsored activities, and differentiated outcomes by sex and age. Two parental work factors primarily influenced adolescent's well‐being, parental paygrade/rank and engagement in military‐sponsored activities. Parental paygrade/rank was the only factor uniformly related to poorer well‐being, and this variable likely represents a more complex set of family circumstances. Engaging in military‐sponsored activities served as a resource and was related to enhanced well‐being. Individual‐level differences and implications for social workers are discussed.     

Personal Efficacy, the Information Environment, and Attitudes Toward Global Warming and Climate Change in the United States

Despite the growing scientific consensus about the risks of global warming and climate change, the mass media frequently portray the subject as one of great scientific controversy and debate. And yet previous studies of the mass public's subjective assessments of the risks of global warming and climate change have not sufficiently examined public informedness, public confidence in climate scientists, and the role of personal efficacy in affecting global warming outcomes. By examining the results of a survey on an original and representative sample of Americans, we find that these three forces—informedness, confidence in scientists, and personal efficacy—are related in interesting and unexpected ways, and exert significant influence on risk assessments of global warming and climate change. In particular, more informed respondents both feel less personally responsible for global warming, and also show less concern for global warming. We also find that confidence in scientists has unexpected effects: respondents with high confidence in scientists feel less responsible for global warming, and also show less concern for global warming. These results have substantial implications for the interaction between scientists and the public in general, and for the public discussion of global warming and climate change in particular.     

Arbitrage Pricing Theory as a Restricted Nonlinear Multivariate Regression Model Iterated Nonlinear Seemingly Unrelated Regression Estimates

By replacing the unknown random factors of factor analysis with observed macroeconomic variables, the arbitrage pricing theory (APT) is recast as a multivariate nonlinear regression model with across-equation restrictions. An explicit theoretical justification for the inclusion of an arbitrary, well-diversified market index is given. Using monthly returns on 70 stocks, iterated nonlinear seemingly unrelated regression techniques are employed to obtain joint estimates of asset sensitivities and their associated APT risk “prices.” Without the assumption of normally distributed errors, these estimators are strongly consistent and asymptotically normal. With the additional assumption of normal errors, they are also full-information maximum likelihood estimators. Classical asymptotic nonlinear nested hypothesis tests are supportive of the APT with measured macroeconomic factors.     

The power piecewise exponential model

In this paper an extension of the piecewise exponential distribution based on the distribution of the maximum of a random sample is considered. Properties of its density and hazard function are investigated. Maximum likelihood inference is discussed and the Fisher information matrix is identified. Results of two real data applications are reported, where model fitting is implemented by using maximum likelihood. The applications illustrate the better performance of the new distribution when compared with other recently proposed alternative models.     

Emotion Regulation in Context: Situational Effects on Infant and Caregiver Behavior

Emotion regulation is an important developmental task of the early years of life. However, situational effects are rarely examined. In this study, we evaluated situational effects on 7‐month‐olds' and their mothers' emotional expression and interactive regulation behavior, individual differences across situations, and intercorrelations within situations. Mother‐infant dyads (N = 225) were observed interacting during episodes from play, teaching, and still‐face situations that varied along 2 developmentally salient dimensions: emotional challenge (low vs. high), and attentional focus (face‐to‐face vs. object). Attentional focus affected mothers' behavior, whereas both challenge and attentional focus affected infants. Associations between mother and infant behaviors varied in each situation. High‐challenge situations provided more consistent individual differences in infants and more negative behavior from mothers. Findings have implications for appropriate assessment of emotion regulation in infancy.