The Structure of Issue Voting in Postindustrial Democracies

Issues matter for elections. The issue environment, however, varies across political campaigns as well as across countries. How does the issue environment structure the vote? Is the issue space single‐ or multidimensional? Do issues vary in terms of salience across parties or nations? This article addresses these questions using an original dataset of mass and elite policy positions covering the United States and nine other industrialized nations. Results show that while the traditional language of politics—expressed as the left/right divide—still resonates, the issue space is not single dimensional but two dimensional. Issues associated with globalization represent a crosscutting divide, which complicates the voter's decision. Further, the salience of an issue to a party varies as a function of the party's type, size, and age. This article shows how a cross‐national approach provides perspective on how voter decision making operates in different country contexts.     

Addressing potential prior‐data conflict when using informative priors in proof‐of‐concept studies

Bayesian methods are increasingly used in proof‐of‐concept studies. An important benefit of these methods is the potential to use informative priors, thereby reducing sample size. This is particularly relevant for treatment arms where there is a substantial amount of historical information such as placebo and active comparators. One issue with using an informative prior is the possibility of a mismatch between the informative prior and the observed data, referred to as prior‐data conflict. We focus on two methods for dealing with this: a testing approach and a mixture prior approach. The testing approach assesses prior‐data conflict by comparing the observed data to the prior predictive distribution and resorting to a non‐informative prior if prior‐data conflict is declared. The mixture prior approach uses a prior with a precise and diffuse component. We assess these approaches for the normal case via simulation and show they have some attractive features as compared with the standard one‐component informative prior. For example, when the discrepancy between the prior and the data is sufficiently marked, and intuitively, one feels less certain about the results, both the testing and mixture approaches typically yield wider posterior‐credible intervals than when there is no discrepancy. In contrast, when there is no discrepancy, the results of these approaches are typically similar to the standard approach. Whilst for any specific study, the operating characteristics of any selected approach should be assessed and agreed at the design stage; we believe these two approaches are each worthy of consideration. Copyright © 2015 John Wiley & Sons, Ltd.     

Staying safe while consuming alcohol: a qualitative study of the protective strategies and informational needs of college freshmen

OBJECTIVE: In this qualitative study, the authors examined how students attempt to minimize harm to themselves and others when drinking. PARTICIPANTS: The authors recruited freshmen at a large, mid-Atlantic US public university during the fall semester of 2005 to participate in 8 focus groups. METHODS: The moderator's guide was developed through an iterative process that included input from experts and pilot testing. The researchers audiotaped focus group conversations, transcribed them, and subjected them to an interrater reliability check. Analysis was based on the framework of Information-Motivation-Behavioral Skills Model and a phenomenological approach. RESULTS: College students have a repertoire of coping strategies they use in an attempt to safeguard themselves and their friends from harm when drinking. Strategies encompass planning a safe context for drinking, using safety measures to minimize harm when drinking, and taking care of someone who has consumed too much alcohol. CONCLUSIONS: A harm-reduction focus that acknowledges and builds on existing protective strategies may be a promising avenue for alcohol interventions.     

The Research Environment Norm Inventory (RENI): a study of integrity in research administrative systems

University research administrators have been generally ignored in basic studies of research integrity. Hensley noted that research administrators are "essential... to the achievement of the specific missions of postsecondary institutions... and to science and the academic infrastructure". The following study sought to extend the scope of research on research integrity to research administrative structures with a new instrument called the Research Environment Norm Inventory or RENI. University research administrators and their professional association were targeted for data collection. Evidence suggested that research administration in the United States supports integrity in the research environment through: (1) respect for community; (2) respect for institutional boundaries; (3) professionalism; (4) respect for authority structures; (5) sensitivity to system conflicts. The study suggested that integrity structures are dictated largely by the institutional settings and environments.     

Modeling Demand For Unionization With Nontraditional Data Analysis Methods

Upon reviewing the extant literature on determinants of unionism, it becomes clear that many areas that have had a plethora of research attention do not converge upon singularly directional findings. This study explores a potential cause of such an apparent anomaly: nonlinearity of data. An exploratory examination of correlation coefficients among typical union determinant variables seems to show different patterns of relationships at different levels of union demand. Thus, a break from traditional linear data analysis techniques is explored in the interest of explaining more variance with typical, theoretically derived variables by using neural network analysis. Results of analyses on industry level data reveal that using neural network analysis to model union demand explained over four times as much variance as multiple regression analysis.     

The Impact of Learning and Labor Attrition on Worker Flexibility in Dual Resource Constrained Job Shops

This study investigates the impact of worker learning, worker flexibility, and labor attrition on the system performance of a dual resource constrained (DRC) job-shop. The effects of learning and labor attrition have not been previously addressed in DRC literature. Results from the study, consistent with previous literature, show that the greatest benefits are achieved when inter-departmental worker flexibility is incrementally introduced into the system. In addition, the learning environment, which depends on the initial processing time of jobs and the learning rates of workers, is shown to impact the acquisition of flexibility. The study also shows that the impact of labor attrition on system performance under certain shop conditions may be significant.     

Capturing temporal dynamics of fear behaviors on a moment‐to‐moment basis

Identifying patterns of fearful behaviors early and accurately is essential to identify children who may be at increased risk for psychopathology. Previous work focused on the total amount of fear by using composites across time. However, considering the temporal dynamics of fear expression might offer novel insights into the identification of children at risk. One hundred and twenty‐five toddlers participated in high‐ and low‐fear tasks. Data were modeled using a novel two‐step approach. First, a hidden Markov model estimated latent fear states and transitions across states over time. Results revealed children's behavior was best represented by six behavioral states. Next, these states were analyzed using sequence clustering to identify groups of children with similar dynamic trajectories through the states. A four‐cluster solution found groups of children varied in fear response and regulation process: “external regulators” (using the caregiver as a regulation tool), “low reactive” (low reaction to stimulus), “fearful explorers” (managing their own internal state with minimal assistance from the caregiver), and “high fear” (fearful/at‐caregiver state regardless of task). The combination of analytic tools enabled fine‐grained examination of the processes of fearful temperament. These insights may help prevention programs target behaviors that perpetuate anxious behavior in the moment.     

Sensitivity Analysis in Linear Programming Models with Common Inputs

The importance of sensitivity analysis information in linear programming has been stressed in the management science literature for some time. Indeed, Gal [3] has devoted an entire text to just this issue. Linear programs with common inputs (cost coefficients or right-hand-side values) present a problem in that classical sensitivity analysis does not allow for the simultaneous changes required to determine the sensitivity of these models to common inputs. We first survey the approaches previously developed for simultaneous-change sensitivity analysis and cast them in the framework of the special common input case. These general techniques are compared to a simple aggregate variable technique that has not received attention in the literature.     

The Popular Kids Don't Matter: Centrality and Influence on Adolescent Behavior

This study examines the widely held belief that socially central individuals are disproportionately influential in their networks. Using data from the National Longitudinal Study of Adolescent Health, it models the association between four behavioral outcomes and two distinct specifications of the behaviors' relationship to network prominence. This study finds little evidence that sociometrically central individuals are more influential than randomly chosen peers from the same network when predicting drinking, smoking, and sports participation. Students resemble their peers in systematic ways, but it is unlikely that this is because central students serve as a reference for the group or because students adjust their actions based on the social rewards that they observe given their position in a social network.