Analysis of Regional Scale Risk of Whirling Disease in Populations of Colorado and Rio Grande Cutthroat Trout Using a Bayesian Belief Network Model

Introduction and spread of the parasite Myxobolus cerebralis, the causative agent of whirling disease, has contributed to the collapse of wild trout populations throughout the intermountain west. Of concern is the risk the disease may have on conservation and recovery of native cutthroat trout. We employed a Bayesian belief network to assess probability of whirling disease in Colorado River and Rio Grande cutthroat trout (Oncorhynchus clarkii pleuriticus and Oncorhynchus clarkii virginalis, respectively) within their current ranges in the southwest United States. Available habitat (as defined by gradient and elevation) for intermediate oligochaete worm host, Tubifex tubifex, exerted the greatest influence on the likelihood of infection, yet prevalence of stream barriers also affected the risk outcome. Management areas that had the highest likelihood of infected Colorado River cutthroat trout were in the eastern portion of their range, although the probability of infection was highest for populations in the southern, San Juan subbasin. Rio Grande cutthroat trout had a relatively low likelihood of infection, with populations in the southernmost Pecos management area predicted to be at greatest risk. The Bayesian risk assessment model predicted the likelihood of whirling disease infection from its principal transmission vector, fish movement, and suggested that barriers may be effective in reducing risk of exposure to native trout populations. Data gaps, especially with regard to location of spawning, highlighted the importance in developing monitoring plans that support future risk assessments and adaptive management for subspecies of cutthroat trout.     

Earnings Differentials of Seafarers

I investigate the earnings differentials among union and nonunion seafarers, across seafarer occupations, and with respective to other transport operatives. The empirical results suggest that the union and nonunion weekly earnings of captains/mates are comparable, and the union earnings gap for sailors/deckhands is positive. The union (nonunion) weekly earnings of captains/mates are 14.7 (30.5) percent greater than those of sailors/deckhands; the union weekly earnings of captains/mates (sailors/deckhands) are 12.6% greater (9.5% less) than those of truck drivers; and the nonunion weekly earnings of captains/mates (sailors/deckhands) are 33.0% greater (6.2% less) than those of truck drivers. The sailor/deckhand and truck driver earnings differentials are contrary to the general belief that the earnings of truck drivers are less than those of other operative occupations involved in transporting intermodal cargo.

Modeling population and subject-specific growth in a latent trait measured by multiple instruments over time using a hierarchical Bayesian framework

Psychometric growth curve modeling techniques are used to describe a person’s latent ability and how that ability changes over time based on a specific measurement instrument. However, the same instrument cannot always be used over a period of time to measure that latent ability. This is often the case when measuring traits longitudinally in children. Reasons may be that over time some measurement tools that were difficult for young children become too easy as they age resulting in floor effects or ceiling effects or both. We propose a Bayesian hierarchical model for such a scenario. Within the Bayesian model we combine information from multiple instruments used at different age ranges and having different scoring schemes to examine growth in latent ability over time. The model includes between-subject variance and within-subject variance and does not require linking item specific difficulty between the measurement tools. The model’s utility is demonstrated on a study of language ability in children from ages one to ten who are hard of hearing where measurement tool specific growth and subject-specific growth are shown in addition to a group level latent growth curve comparing the hard of hearing children to children with normal hearing.KEYWORDS: Bayesian hierarchical models, psychometric modeling, language ability, growth curve modeling, longitudinal analysis     

Methods for spatial and temporal land use and land cover assessment for urban ecosystems and application in the greater Baltimore-Chesapeake region

Understanding contemporary urban landscapes requires multiple sets of spatially and temporally compatible data that can integrate historical land use patterns and disturbances to land cover. This paper presents three principal methods: (1) core analysis; (2) historic mapping; and (3) gradient analysis, to link spatial and temporal data for urban ecosystems and applies their use in the Baltimore-Chesapeake region. Paleoecological evidence derived from the geochronology of sediment cores provides data on long-term as well as recent changes in vegetative land cover. This information, combined with contemporary vegetation maps, provides a baseline for conducting trend analyses to evaluate urbanization of the landscape. A 200-year historical land use database created from historical maps, census data, and remotely sensed data provides a spatial framework for investigating human impacts on the region. A geographic information system (GIS) integrates core analyses with historic data on land use change to yield a comprehensive land use and land cover framework and rates of change. These data resources establish the regional foundation for investigating the ecological components of an urban ecosystem. Urban-rural gradient analyses and patch analyses are proposed as the most appropriate methods for studying the urban ecosystem as they link ecological and social patterns and processes for varying degrees of urbanization.     

Service diversification and growth of professional service firms

This study investigates the impact of service diversification on the rate and mode of firm growth in professional service firms (PSFs). Drawing on the extant PSF literature, we identify differing views regarding the growth impact of service diversification. Specifically, some scholars suggest that the external client benefits associated with service diversification should allow PSFs to expand revenues at a rapid pace and pursue less merger and acquisition activity, whereas others imply that increased diversification can cause internal challenges with respect to learning costs, coordination and innovation that can limit the rate of revenue growth and encourage more mergers and acquisitions. We test these competing views using longitudinal data on 137 accounting firms and cross-sectional data on 125 law firms and find that service diversification is negatively associated with the rate of firm revenue growth and positively associated with the use of mergers and acquisitions.     

Harm reduction for cannabis: Factor analysis of a protective behavioral strategies survey

Objective: To examine the psychometric properties of a measure of cannabis-specific Protective Behavioral Strategies (PBS), which assesses ways in which students may reduce cannabis-related risk. Participants: Respondents to the American College Health Association – National College Health Assessment II (N = 580) during Spring 2015. Methods: Exploratory Factor Analysis (EFA) and Exploratory Structural Equation Modeling (ESEM) were used to identify and replicate the factor structure of the measure. Results: Results support a four-factor model (Respiratory Health, Frequency/Quantity, Socializing, and General Health) with close approximate fit (Χ² (310) = 565.96, p < .001, RMSEA = .038 (.033, .043; 90% CI), CFI = .961, TLI = .929, SRMR = .033). Support for the convergent validity and construct validity of the measure was also found. Conclusions: This is the initial step in the development of a standard, psychometrically validated measure of cannabis PBS that has the potential to inform future research and interventions.     

VARIANCE FUNCTION REGRESSIONS FOR STUDYING INEQUALITY

Regression-based studies of inequality model only between-group differences, yet often these differences are far exceeded by residual inequality. Residual inequality is usually attributed to measurement error or the influence of unobserved characteristics. We present a model, called  variance function regression , that includes covariates for both the mean and variance of a dependent variable. In this model, the residual variance is treated as a target for analysis. In analyses of inequality, the residual variance might be interpreted as measuring risk or insecurity. Variance function regressions are illustrated in an analysis of panel data on earnings among released prisoners in the National Longitudinal Survey of Youth. We extend the model to a decomposition analysis, relating the change in inequality to compositional changes in the population and changes in coefficients for the mean and variance. The decomposition is applied to the trend in U.S. earnings inequality among male workers, 1970 to 2005.     

Empirical Application of Skinner’s Verbal Behavior to Interventions for Children with Autism: A Review

The Analysis of Verbal Behavior - Sundberg and Michael (2011) reviewed the contributions of Skinner’s (1957) Verbal Behavior to the treatment of language delays in children with autism...     

College students coping with interpersonal stress: Examining a control-based model of coping

Objective: The ways that college students cope with stress, particularly interpersonal stress, may be a critical factor in determining which students are at risk for impairing mental health disorders. Using a control-based model of coping, the present study examined associations between interpersonal stress, coping strategies, and symptoms. Participants: A total of 135 undergraduate students from 2 universities. Methods: Interpersonal stress, coping strategies, depression, anxiety, and somatization were assessed via self-report. Results: Students reporting more interpersonal stress reported more depression, anxiety, and somatization, and they reported less use of engagement coping strategies and greater use of disengagement coping strategies. Engagement coping strategies accounted for a significant portion of the association between interpersonal stress and mental health symptoms. Unexpectedly, coping strategies did not moderate the association between stress and mental health symptoms. Conclusion: Interventions designed to improve students' coping strategies may be an effective way to reduce mental health problems on college campuses.