The effect of poor parenting on male and female dating violence perpetration and victimization

This study examines the effects of poor parenting on dating violence perpetration and victimization among approximately 900 males and females from the National Longitudinal Survey of Adolescent Health (Add Health). Results revealed that more physical abuse and low parental warmth were linked to greater substance use and higher rates of delinquency. In addition, low parental warmth, more neglect, and greater delinquency had positive direct effects on dating violence perpetration, whereas more physical abuse, low parental warmth, and increased delinquency were all positively associated with dating violence victimization. Finally, delinquency mediated the link between low parental warmth and dating violence perpetration and victimization. The results provide some support for both social learning theory and an antisocial orientation perspective.     

A Component Analysis of the Impact of Evaluative and Objective Feedback on Performance

Despite the frequency with which performance feedback interventions are used in organizational behavior management, component analyses of such feedback are rare. It has been suggested that evaluation of performance and objective details about performance are two necessary components for performance feedback. The present study was designed to help clarify which components are required for maximal effectiveness by comparing four conditions: (a) combined evaluative and objective feedback, (b) evaluative feedback alone, (c) objective feedback alone, and (d) no feedback. A total of 105 undergraduate students were recruited to work on a simulated bank check processing task while being exposed to one of the four feedback conditions. The number of checks correctly processed served as the dependent variable. Results suggest that a combination of objective and evaluative feedback is necessary for maximal performance.     

Effectiveness of Interactive Computer-Based Instruction: A Review of Studies Published Between 1995 and 2007

Computer-based instruction (CBI) has been growing rapidly as a training tool in organizational settings, but close attention to behavioral factors has often been neglected. CBI represents a promising instructional advancement over current training methods. This review article summarizes 12 years of comparative research in interactive computer-based instruction relevant to employee training techniques. The results demonstrate that CBI is an effective and viable training technique, and several areas in need of further examination are detailed.     

Further specification of the leader political skill–leadership effectiveness relationships: Transformational and transactional leader behavior as mediators

The present investigation was a three-source test of the intermediate linkages in the leader political skill–leader effectiveness and follower satisfaction relationships, which examined transformational and transactional (i.e., contingent reward behavior) leader behavior as mediators. Data from 408 leaders (headmasters) and 1429 followers (teachers) of state schools in the western part of Germany participated in this research. The results of mediation analyses, based on bias-corrected bootstrapping confidence intervals, provided support for the hypotheses that political skill predicts both transformational and transactional leader behavior, beyond other established predictors, and that transformational and transactional leader behavior mediate the relationships between leader political skill and leadership effectiveness. The contributions to theory and research, strengths and limitations, directions for future research, and practical implications are discussed.     

Restricted minimax robust designs for misspecified regression models

The authors propose and explore new regression designs. Within a particular parametric class, these designs are minimax robust against bias caused by model misspecification while attaining reasonable levels of efficiency as well. The introduction of this restricted class of designs is motivated by a desire to avoid the mathematical and numerical intractability found in the unrestricted minimax theory. Robustness is provided against a family of model departures sufficiently broad that the minimax design measures are necessarily absolutely continuous. Examples of implementation involve approximate polynomial and second order multiple regression.     

Complexity and Competition

Extensive‐form market games typically have a large number of noncompetitive equilibria. In this paper, we argue that the complexity of noncompetitive behavior provides a justification for competitive equilibrium in the sense that if rational agents have an aversion to complexity (at the margin), then maximizing behavior will result in simple behavioral rules and hence in a competitive outcome. For this purpose, we use a class of extensive‐form dynamic matching and bargaining games with a finite number of agents. In particular, we consider markets with heterogeneous buyers and sellers and deterministic, exogenous, sequential matching rules, although the results can be extended to other matching processes. If the complexity costs of implementing strategies enter players’ preferences lexicographically with the standard payoff, then every equilibrium strategy profile induces a competitive outcome.     

Quantifying Potential Human Health Impacts of Animal Antibiotic Use: Enrofloxacin and Macrolides in Chickens

Use of similar or identical antibiotics in both human and veterinary medicine has come under increasing scrutiny by regulators concerned that bacteria resistant to animal antibiotics will infect people and resist treatment with similar human antibiotics, leading to excess illnesses and deaths. Scientists, regulators, and interest groups in the United States and Europe have urged bans on nontherapeutic and some therapeutic uses of animal antibiotics to protect human health. Many regulators and public health experts have also expressed dissatisfaction with the perceived limitations of quantitative risk assessment and have proposed alternative qualitative and judgmental approaches ranging from "attributable fraction" estimates to risk management recommendations based on the precautionary principle or on expert judgments about the importance of classes of compounds in human medicine. This article presents a more traditional quantitative risk assessment of the likely human health impacts of continuing versus withdrawing use of fluoroquinolones and macrolides in production of broiler chickens in the United States. An analytic framework is developed and applied to available data. It indicates that withdrawing animal antibiotics can cause far more human illness-days than it would prevent: the estimated human BENEFIT:RISK health ratio for human health impacts of continued animal antibiotic use exceeds 1,000:1 in many cases. This conclusion is driven by a hypothesized causal sequence in which withdrawing animal antibiotic use increases illnesses rates in animals, microbial loads in servings from the affected animals, and hence human health risks. This potentially important aspect of human health risk assessment for animal antibiotics has not previously been quantified.     

A Periodic Inventory Model for Stocking Modular Components

We study the benefit obtained by exploiting modular product design in fulfilling exogenous demand for both a complete assembly and its components in a service parts inventory system. Our goal is to reduce overall service system costs by allowing assembly and/or disassembly (A/D) to occur at some unit cost per A/D action. In an extensive set of computational experiments, we compare a naïve stocking and operating policy that treats all items independently and ignores the modular product structure and related A/D capability to the optimal base stock policy, and to a policy that allows A/D from the naïve stocking levels. While extensive computational analysis shows that the optimal base stock policy improves the system cost between 3 to 26% over the naïve approach, simply allowing A/D from the naïve stocking levels captures a significant portion (an average of 67%) of the naïve–optimal gap. Our computational results demonstrate that the optimization shifts the component‐assembly mix from the naïve levels and that limiting A/D capacity affects this mix. Limiting A/D capacity can actually increase the expected number of A/D actions (versus the uncapacitated case), since the optimization shifts stocking levels to reduce the probability that “too many” actions will be required.     

Rethinking Politics for a Green Economy: A Political Approach to Radical Reform

Because the process of achieving a green economy is bound to be political, it is important how politics is understood. This essay employs a three-dimensional model of politics (functional, constitutive, performative) in developing an approach to radical reform that accentuates political potentialities—understood in terms of debate, open exchanges of differing opinions. By exploring a central tension between the formal economy (associated with administrative and policy arenas in modern society) and the informal economy (associated with the enhancement of community), the argument concludes that achieving a green economy involves a key role not simply for the rational economic individual or the cooperative community member, but also for the citizen.     

Parameterization and inference for nonparametric regression problems

We consider local likelihood or local estimating equations, in which a multivariate function () is estimated but a derived function () of () is of interest. In many applications, when most naturally formulated the derived function is a non-linear function of (). In trying to understand whether the derived non-linear function is constant or linear, a problem arises with this approach: when the function is actually constant or linear, the expectation of the function estimate need not be constant or linear, at least to second order. In such circumstances, the simplest standard methods in nonparametric regression for testing whether a function is constant or linear cannot be applied. We develop a simple general solution which is applicable to nonparametric regression, varying-coefficient models, nonparametric generalized linear models, etc. We show that, in local linear kernel regression, inference about the derived function () is facilitated without a loss of power by reparameterization so that () is itself a component of (). Our approach is in contrast with the standard practice of choosing () for convenience and allowing ()> to be a non-linear function of (). The methods are applied to an important data set in nutritional epidemiology.