Some properties of Lin–Wong divergence on the past lifetime data

Measures of statistical divergence are used to assess mutual similarities between distributions of multiple variables through a variety of methodologies including Shannon entropy and Csiszar divergence. Modified measures of statistical divergence are introduced throughout the present article. Those modified measures are related to the Lin–Wong (LW) divergence applied on the past lifetime data. Accordingly, the relationship between Fisher information and the LW divergence measure was explored when applied on the past lifetime data. Throughout this study, a number of relations are proposed between various assessment methods which implement the Jensen–Shannon, Jeffreys, and Hellinger divergence measures. Also, relations between the LW measure and the Kullback–Leibler (KL) measures for past lifetime data were examined. Furthermore, the present study discusses the relationship between the proposed ordering scheme and the distance interval between LW and KL measures under certain conditions.     

Estimation of the cumulative incidence function under multiple dependent and independent censoring mechanisms

Competing risks occur in a time-to-event analysis in which a patient can experience one of several types of events. Traditional methods for handling competing risks data presuppose one censoring process, which is assumed to be independent. In a controlled clinical trial, censoring can occur for several reasons: some independent, others dependent. We propose an estimator of the cumulative incidence function in the presence of both independent and dependent censoring mechanisms. We rely on semi-parametric theory to derive an augmented inverse probability of censoring weighted (AIPCW) estimator. We demonstrate the efficiency gained when using the AIPCW estimator compared to a non-augmented estimator via simulations. We then apply our method to evaluate the safety and efficacy of three anti-HIV regimens in a randomized trial conducted by the AIDS Clinical Trial Group, ACTG A5095.     

Development of predictive signatures for treatment selection in precision medicine with survival outcomes

For survival endpoints in subgroup selection, a score conversion model is often used to convert the set of biomarkers for each patient into a univariate score and using the median of the univariate scores to divide the patients into biomarker‐positive and biomarker‐negative subgroups. However, this may lead to bias in patient subgroup identification regarding the 2 issues: (1) treatment is equally effective for all patients and/or there is no subgroup difference; (2) the median value of the univariate scores as a cutoff may be inappropriate if the sizes of the 2 subgroups are differ substantially. We utilize a univariate composite score method to convert the set of patient's candidate biomarkers to a univariate response score. We propose applying the likelihood ratio test (LRT) to assess homogeneity of the sampled patients to address the first issue. In the context of identification of the subgroup of responders in adaptive design to demonstrate improvement of treatment efficacy (adaptive power), we suggest that subgroup selection is carried out if the LRT is significant. For the second issue, we utilize a likelihood‐based change‐point algorithm to find an optimal cutoff. Our simulation study shows that type I error generally is controlled, while the overall adaptive power to detect treatment effects sacrifices approximately 4.5% for the simulation designs considered by performing the LRT; furthermore, the change‐point algorithm outperforms the median cutoff considerably when the subgroup sizes differ substantially.     

A penalized likelihood method for nonseparable space–time generalized additive models

In this paper, we study space–time generalized additive models. We apply the penalyzed likelihood method to fit generalized additive models (GAMs) for nonseparable spatio-temporal correlated data in order to improve the estimation of the response and smooth terms of GAMs. The results show that our space–time generalized additive models estimated response and smooth terms reasonable well, and in addition, the mean squared error, mean absolute deviation and coverage intervals improved considerably compared to the classic GAM. An application on particulate matter concentration in the North-Italian region of Piemonte is also presented.     

Demographic Comparison of American Individuals in Polyamorous and Monogamous Relationships

Research on polyamorous relationships has increased substantially over the past decade. This work has documented how polyamory is practiced and why individuals might pursue such arrangements. However, there is a lack of a systematic investigation of who is in polyamorous relationships and how they might differ from individuals in monogamous relationships. The present study is one of the first to address this by comparing the demographic backgrounds of individuals in polyamorous (N = 2,428) and monogamous (N = 539) relationships in the United States. Compared to participants in monogamous relationships, those in polyamorous relationships were more likely to report minority sexual identities. Despite similar age distributions, individuals in polyamorous relationships were more likely to report being in a civil union, being divorced, and earning less than $40,000 per year compared to individuals in monogamous relationships. People in polyamorous relationships were also more likely to select “other” options for most demographic characteristics, suggesting that they tend to choose less traditional response options in general. The current research highlights several demographic differences that need to be considered and potentially controlled for in future comparisons of polyamorous and monogamous relationships.     

Coercive controlling behaviors in intimate partner violence in male same-sex relationships:A mixed-methods study

Using mixed methods, we explored the role of coercive controlling behaviors in a high-risk sample of 126 men in violent same-sex relationships. Contrary to a prediction that separate factors of physical violence and coercive control might emerge, a simple principle components analysis supported that male same-sex relationship intimate partner violence (IPV) is essentially unidimensional. Qualitative narratives supported a single latent factor solution of violence, and that coercive controlling behaviors better detect IPV dynamics within the same violent encounters (i.e., weapon use), even when compared to profiles defined by physical violence. Narratives also highlighted gender-different tactics of coercion used, underscoring importance of context-based assessments.     

Meningococcal serogroup B outbreak response University of Wisconsin-Madison

A meningococcal serogroup B (MenB) outbreak at a large public university prompted an emergency response to immunize undergraduates. Objective: To report on a successful meningococcal serogroup B (MenB) vaccine clinic response at a large public university. Methods: We assembled the team leaders to write this case report. Results: Activation of the emergency plan and points of dispensing required cooperation of many units on campus under the leadership of university health officials with support from Centers for Disease Control and Prevention, state division of public health and the city-county health department. Significant efforts to provide consistent messages to students and parents regarding the outbreak and the availability of the MenB vaccines were made. Volunteers were recruited to staff the clinics alongside university healthcare providers. Over 22,000 doses of vaccine were administered. Conclusion: We report our experience and lessons learned which may be helpful to universities in preventing and responding to disease outbreaks.     

Change Communication in Public Sector Cutback Management

Public Organization Review - Budget cuts in public sector organizations create additional strain for employees, often contributing to uncertainty, rumors, and low morale. This study examines the...     

Sexual Victimization and Sex-Related Drinking Motives: How Protective is Emotion Regulation?

One in five college women experience sexual victimization (SV), and SV severity is associated with subsequent psychological distress, including sex-related distress. SV severity may also be associated with drinking motives to cope with sex-related distress and to enhance sex (sex-related drinking motives [SRDMs]), particularly if individuals suffer from emotion regulation (ER) difficulties. College women (N = 151) completed a survey assessment of ER, SV history, childhood sexual abuse (CSA), and SRDMs. Twelve regression models assessed six facets of ER as moderators between SV severity and SRDMs. Among women with no or low levels of prior SV severity, women with greater access to ER strategies were less likely to endorse drinking to cope SRDMs. At higher levels of SV severity, women at all levels of access to ER strategies were equally likely to endorse drinking to cope SRDMs, suggesting that access to ER strategies did not mitigate motivations to drink to cope with sex-related distress for these women. Women with severe SV histories may benefit from interventions that build on existing ER strengths or address other factors. However, greater access to ER strategies may serve as a protective factor against SRDMs when SV severity is low.