Examining Localized Patterns of Air Quality Perception in Texas: A Spatial and Statistical Analysis

Environmental and human health issues associated with outdoor air pollution, such as ozone, sulfur dioxide, and other pollutants in metropolitan regions, are an area of growing concern for both policy officials and the general public. Increasing attention from the news media, new health data, and public debate over the effectiveness of clean air regulations have raised the importance of air quality in the public consciousness. While public perceptions of air quality have been studied thoroughly dating back to the 1960s, little empirical research has been conducted to explain the spatial aspects of these perceptions, particularly at the local level. Although recent studies suggest characteristics of local setting are important in shaping perceptions of air quality, the roles of proximity, neighborhood characteristics, and location have not been clarified. This study seeks to improve understanding of the major factors shaping public perceptions of air quality by examining the spatial pattern of local risk perception, the role of socioeconomic characteristics in forming these perceptions, and the relationship between perceived and scientifically measured air pollution. First, we map the spatial pattern of local air quality perceptions using Geographic Information Systems (GIS) across the Dallas and Houston metropolitan areas. Next, we explain these perceptions through local contextual factors using both bivariate correlations and multivariate regression analysis. Results indicate that perceptions of air quality in the study areas are not significantly correlated with air quality based on readings of air monitoring stations. Instead, perceptions appear to be influenced by setting (urban vs. rural), state identification, access to information, and socioeconomic characteristics such as age, race, and political identification. We discuss the implications of the findings and provide direction on how further research can provide a deeper understanding of the local contextual factors influencing public perceptions.     

Split Hamiltonian Monte Carlo

We show how the Hamiltonian Monte Carlo algorithm can sometimes be speeded up by “splitting” the Hamiltonian in a way that allows much of the movement around the state space to be done at low computational cost. One context where this is possible is when the log density of the distribution of interest (the potential energy function) can be written as the log of a Gaussian density, which is a quadratic function, plus a slowly-varying function. Hamiltonian dynamics for quadratic energy functions can be analytically solved. With the splitting technique, only the slowly-varying part of the energy needs to be handled numerically, and this can be done with a larger stepsize (and hence fewer steps) than would be necessary with a direct simulation of the dynamics. Another context where splitting helps is when the most important terms of the potential energy function and its gradient can be evaluated quickly, with only a slowly-varying part requiring costly computations. With splitting, the quick portion can be handled with a small stepsize, while the costly portion uses a larger stepsize. We show that both of these splitting approaches can reduce the computational cost of sampling from the posterior distribution for a logistic regression model, using either a Gaussian approximation centered on the posterior mode, or a Hamiltonian split into a term that depends on only a small number of critical cases, and another term that involves the larger number of cases whose influence on the posterior distribution is small.     

The Detection of Influential Observations for Allocation,Separation, and the Determination of Probabilities in a Bayesian Framework

Normal theory separation and allocation problems are discussed from a predictive point of view. Influence statistics are defined and employed to ascertain the impact that particular observations will have on the inferential goals—allocation of future observations, separation between populations, and the determination of probabilities for future cases. Methods are illustrated on a collection of financial data taken from Johnson and Wichern (1982).     

The Effect of 21st Century Military Service on Civilian Labor and Educational Outcomes

I estimate the effect of military service during the Afghanistan and Iraq wars on civilian labor and educational outcomes using several empirical methodologies including sibling fixed effects and propensity score matching. Since military occupations and training have changed significantly in the past few decades, these effects may be different than those found in previous studies on veterans of earlier theaters. I find that veteran status increases civilian wages by approximately ten percent for minorities but has little or no effect on whites in this regard. Veterans of all demographic groups are found to be equally employable and equally as satisfied with their civilian occupation as non-veterans. For females and minorities, veteran status substantially increases the likelihood one attempts college. These veterans are found to be more apt to pursue and obtain a two year (associate’s) degree instead of a four year (bachelor’s) degree. Lastly, I find mixed evidence that veteran status increases the likelihood of public sector employment.     

The Probability of Teenage Parenthood: Parental Predictions and Their Accuracy

Teenage parenthood is an often-discussed topic in family economics since it has been shown to affect many outcomes for the teen, child, and household. Using a nationally representative longitudinal panel of American teenagers and their parents, two questions related to the probability of teenage parenthood are examined. First, how do predictions of this occurrence made by the teenager’s parents vary across the population? Second, how does the accuracy of these predictions vary? The actual prevalence and variance of teenage parenthood are also examined, and the determinants of its occurrence are estimated. Among other results, expectations and their accuracy are found to differ substantially across socioeconomic status and some demographics such as race and religion. The average American parent underestimates the probability their child will become a teen parent by only a small amount, but within certain demographic groups this outcome is considerably underestimated, and in others it is overestimated. These differences help explain the variability in teen parenthood effects, and more broadly, the analysis serves as a test of parents’ ability to judge their childrens’ future outcomes.     

An evaluation of physical fitness parameters for graduate students

Although graduate physical therapy students are taught the principles of fitness for incorporation into their professional lives, they have difficulty finding the time to implement these principles during graduate school. The authors studied 3 successive classes of graduate physical therapy students at the beginning and ending of their respective programs. They found that the women's percentages of body fat were significantly greater over the period of the study. The men's lower extremity strength decreased at the slower speeds (60 degrees/second), and the women showed increased strength at the higher speeds (180 and 240 degrees/second, respectively). Male grip strength significantly increased over the period of the study. To decrease students' percentages of body fat and increase their strength, the authors asserted that physical therapy students should be allowed more time to participate in fitness activities during their graduate school years.     

Conservatism of the Accident Sequence Evaluation Program HRA Procedure

This paper presents a limited assessment of the conservatism of the Accident Sequence Evaluation Program (ASEP) human reliability analysis (HRA) procedure described in NUREG/CR-4772. The data for this study are derived from simulator examination reports from the NRC requalification examination cycle for nuclear power plant operators. The ASEP procedure was used to estimate human error probability (HEP) values for critical tasks, and the HEP results were compared with the failure rates observed in the examinations. The ASEP procedure was applied by PNNL operator license examiners who supplemented the limited information in the examination reports with expert judgment based upon their extensive simulator examination experience. Comparison of the average of the ASEP HEP values with the fraction of the population actually failed and demonstrated that the ASEP HEP values are larger (conservative) by a statistically significant average factor of two. Partitioning of tasks into subgroups based on the ASEP HEP values and comparison of the subgroup average ASEP HEP values with observed subgroup failure rates showed little or no conservatism for small ASEP HEP values, but considerable conservatism for larger ASEP HEP values.     

The influence of the economic crisis on quality of care for older people: system readiness for innovation in Europe

The aim of this study is to examine the influence of the recent economic crisis on the quality of long-term care for older people in Belgium and the Netherlands. A mixed-method approach was applied, primarily focused on conducting semi-structured qualitative interviews with health professionals working in a management role in organizations providing long-term care for older people. The results show that Dutch organizations seem to be prepared for the influences of the economic crisis on the quality of its care provision primarily in terms of a sound system readiness. At the same time, Belgian organizations seem to be prepared for the influences of the economic crisis on the quality of its care provision primarily in terms of a favorable sociopolitical context. Comparing two countries allows for reciprocal lesson-drawing. The conclusion drawn in this study is that a sustainable long-term care system requires above all stability and structure.