Risk factors for femicide-suicide in abusive relationships: results from a multisite case control study

The killing of women by men who then take their own lives (femicide-suicide) is the most common form of homicide-suicide. This study identified femicide-suicide risk factors in an 11-city case-control study of femicide in the United States. Perpetrator, victim, relationship, and incident characteristics were analyzed for femicide-suicide cases (n = 67) and controls (n = 356, women living in the community with nonfatal physical abuse) using logistic regression modeling. Two risk factors emerged that were unique to femicide-suicides cases compared to overall femicide risk analyses: prior perpetrator suicide threats and victims having ever been married to the perpetrator.     

HAC Corrections for Strongly Autocorrelated Time Series

Applied work routinely relies on heteroscedasticity and autocorrelation consistent (HAC) standard errors when conducting inference in a time series setting. As is well known, however, these corrections perform poorly in small samples under pronounced autocorrelations. In this article, I first provide a review of popular methods to clarify the reasons for this failure. I then derive inference that remains valid under a specific form of strong dependence. In particular, I assume that the long-run properties can be approximated by a stationary Gaussian AR(1) model, with coefficient arbitrarily close to one. In this setting, I derive tests that come close to maximizing a weighted average power criterion. Small sample simulations show these tests to perform well, also in a regression context.     

Estimating Noncancer Uncertainty Factors: Are Ratios NOAELs Informative?

The prominent role of animal bioassay evidence in environmental regulatory decisions compels a careful characterization of extrapolation uncertainties. In noncancer risk assessment, uncertainty factors are incorporated to account for each of several extrapolations required to convert a bioassay outcome into a putative subthreshold dose for humans. Measures of relative toxicity taken between different dosing regimens, different endpoints, or different species serve as a reference for establishing the uncertainty factors. Ratios of no observed adverse effect levels (NOAELs) have been used for this purpose; statistical summaries of such ratios across sets of chemicals are widely used to guide the setting of uncertainty factors. Given the poor statistical properties of NOAELs, the informativeness of these summary statistics is open to question. To evaluate this, we develop an approach to calibrate the ability of NOAEL ratios to reveal true properties of a specified distribution for relative toxicity. A priority of this analysis is to account for dependencies of NOAEL ratios on experimental design and other exogenous factors. Our analysis of NOAEL ratio summary statistics finds (1) that such dependencies are complex and produce pronounced systematic errors and (2) that sampling error associated with typical sample sizes (50 chemicals) is non-negligible. These uncertainties strongly suggest that NOAEL ratio summary statistics cannot be taken at face value; conclusions based on such ratios reported in well over a dozen published papers should be reconsidered.     

Updating Uncertainty in an Integrated Risk Assessment: Conceptual Framework and Methods

Bayesian methods are presented for updating the uncertainty in the predictions of an integrated Environmental Health Risk Assessment (EHRA) model. The methods allow the estimation of posterior uncertainty distributions based on the observation of different model outputs along the chain of the linked assessment framework. Analytical equations are derived for the case of the multiplicative lognormal risk model where the sequential log outputs (log ambient concentration, log applied dose, log delivered dose, and log risk) are each normally distributed. Given observations of a log output made with a normally distributed measurement error, the posterior distributions of the log outputs remain normal, but with modified means and variances, and induced correlations between successive log outputs and log inputs. The analytical equations for forward and backward propagation of the updates are generally applicable to sums of normally distributed variables. The Bayesian Monte-Carlo (BMC) procedure is presented to provide an approximate, but more broadly applicable method for numerically updating uncertainty with concurrent backward and forward propagation. Illustrative examples, presented for the multiplicative lognormal model, demonstrate agreement between the analytical and BMC methods, and show how uncertainty updates can propagate through a linked EHRA. The Bayesian updating methods facilitate the pooling of knowledge encoded in predictive models with that transmitted by research outcomes (e.g., field measurements), and thereby support the practice of iterative risk assessment and value of information appraisals.     

External commercialization of knowledge: Review and research agenda

Companies increasingly make use of external knowledge exploitation, i.e. the commercialization of knowledge assets, although they often perceive considerable difficulties in managing external commercialization tasks. These difficulties are partly due to the imperfections in the markets for knowledge, which may be mastered by adequate management, as examples of various well-known companies show. In combination, these facts point to the need for research into external knowledge exploitation. A thorough analysis of past research confirms this need and shows that the existing literature is highly fragmented. By integrating the main findings of the different research streams, a detailed overview of the literature on external knowledge exploitation is established. The key characteristics of externally leveraging knowledge assets are presented, and a research agenda is set up.     

Issues in the assessment of non-inferiority: perspectives drawn from case studies

Superiority claims for improved efficacy are the backbone of clinical development of new therapies. However, not every new therapy in development allows for such a claim. Some therapies per se do not try to improve efficacy further but concentrate on important aspects in safety or convenience. Such improvements can be equally important to patients, and development strategies should be available for such compounds. A three-arm design with placebo, active control and experimental treatment may be viewed as the golden standard for such compounds; however, it may be difficult if not impossible to add a placebo arm in certain diseases. In such situations, non-inferiority designs are the only development option left. This paper will highlight some of the key issues with such designs in practice and will report experience from two studies from different therapeutic areas intended for regulatory submission.     

Mein(nach-wie-vor-schöner)Prof.de

Tobias Wolbring argues in his replica to our article Mein(schöner)Prof.de (issue 4/2009 of this journal) that the presented empirical analyses would be problematic in several respects. He claims our sample was selective, criticizes the lacking control of relevant confounding variables and our statistical model building. In this response we consider Wolbring’s criticism in detail. We believe we can prove that his points of criticism do not hold after a close investigation. In particular, we think our central substantial conclusions can be maintained.     

Process matters – How strategic decision-making process characteristics impact capital allocation efficiency

We employ strategic decision-making process theory to study the internal capital markets of firms and argue that varying allocation efficiency can result from the configuration of the capital allocation decision-making process. Learning from earlier research on firms' portfolio allocations, we also develop assumptions on interaction effects with firm-level unrelated diversification and environmental dynamics. We test our hypotheses with structural equation modeling on an international sample of large multi-business firms. Our results suggest that process formalization and analytical comprehensiveness have a positive influence on the efficiency of allocation decisions. Another key result is that unrelated diversified portfolios positively moderate the influence of analytical comprehensiveness and formalization, while dynamic environments negatively impact the influence of formal processes but reward managerial involvement.     

Resource utilization as an internal driver of alliance portfolio evolution: The Qatar Airways case (1993–2010)

This article aims to understand the role played by resource utilization levels as a driver of alliance portfolio evolution over time. Based on our theoretical framework and on a case study of Qatar Airways (199.3–2010), we develop insights into the micro-dynamics of resource structuring in firms that possess an alliance portfolio. Our research shows that firms can create either their own or network resources with different deployment modes according to their resource utilization levels to remain profitable. We also emphasize that optimized resource utilization is a key driver of resource-structuring efforts in firms. Finally, we show that based on the focal firm's life cycle phase, the level of resource utilization changes and leads to various resource-structuring mechanisms that can be observed at the alliance portfolio level.     

Urbanization homogenizes the interactions of plant-frugivore bird networks

Urban Ecosystems - Anthropogenic activities are the main cause of habitat loss and fragmentation, which directly affects biodiversity. Disruption in landscape connectivity among populations may...