Age Is But a Number? An Exploration of Age Differences in Episodic Volunteering

VOLUNTAS: International Journal of Voluntary and Nonprofit Organizations - Age has long been understood as a strong demographic determinant of volunteering. However, to date, limited literature...     

Abusive Supervision and Well-Being of Filipino Migrant Workers in Macau: Consequences for Self-Esteem and Heritage Culture Detachment

Abusive supervision in the workplace has been shown to have important direct consequence in work and work relationship, and also indirect consequences to workers’ well-being and relationships outside work. Consequences of abusive supervision have not been studied among migrant workers whose status in the host country of work is dependent on maintaining the work contract. This study investigates abusive supervision in 247 Filipino migrant workers in Macau, who hold temporary work contracts and work visas to engage in various low-skilled work (e.g., domestic helper, security guard, etc.). The study tests a model representing the indirect consequences of abusive supervision on the self-esteem and acculturation orientation of migrant workers, in particular, on the tendency to reject their heritage culture in their attempt to acculturate in the host country. Mediation analysis indicated that abusive supervisory perceptions led to lower self-esteem (b = ?.19), which in turn relates to tendency to reject their heritage culture as part of acculturation (b = ?.45) [indirect effect = .08, 90 % CI .04, .15]. The rejection of heritage culture is interpreted as a coping response to the negative indirect consequences of abusive supervision perceptions that may be partly attributed to being a migrant Filipino worker. The results are discussed in terms of how the acculturation of migrant workers reflects aspects of their well-being that may be adversely affected by vocational-related stress in the host country.     

Multiple event times in the presence of informative censoring: modeling and analysis by copulas

Motivated by a breast cancer research program, this paper is concerned with the joint survivor function of multiple event times when their observations are subject to informative censoring caused by a terminating event. We formulate the correlation of the multiple event times together with the time to the terminating event by an Archimedean copula to account for the informative censoring. Adapting the widely used two-stage procedure under a copula model, we propose an easy-to-implement pseudo-likelihood based procedure for estimating the model parameters. The approach yields a new estimator for the marginal distribution of a single event time with semicompeting-risks data. We conduct both asymptotics and simulation studies to examine the proposed approach in consistency, efficiency, and robustness. Data from the breast cancer program are employed to illustrate this research.

     

The mixed evacuation problem

A dynamic network introduced by Ford and Fulkerson is a directed graph with capacities and transit times on its arcs. The quickest transshipment problem is one of the most fundamental problems in dynamic networks. In this problem, we are given sources and sinks. Then the goal of this problem is to find a minimum time limit such that we can send the right amount of flow from sources to sinks. In this paper, we introduce a variant of this problem called the mixed evacuation problem. This problem models an emergent situation in which people can evacuate on foot or by car. The goal is to organize such a mixed evacuation so that an efficient evacuation can be achieved. In this paper, we study this problem from the theoretical and practical viewpoints. In the first part, we prove the polynomial-time solvability of this problem in the case where the number of sources and sinks is not large, and also prove the polynomial-time solvability and computational hardness of its variants with integer constraints. In the second part, we apply our model to the case study of Minabe town in Wakayama prefecture, Japan.     

The neglected mediating role of self-efficacy in the goal setting process in local public administrations

To analyse the role of self-efficacy in goal setting in public administrations, this study combines goal-setting theory, public service motivation literature and cognitive theory. Using partial least squares structural equation modelling (PLS-SEM), survey data from 105 German civil servants are analysed. The results underline the role of goal setting (represented by goal difficulty and specificity) in determining the self-efficacy of public servants. Public service motivation and goal specificity both increase public servants’ work performance; however, the effects of goal difficulty are negatively mediated by the employee’s self-efficacy. That finding reflects the central role of self-efficacy, which should not be ignored in the goal-setting processes of public administrations.     

A new long-term survival model with dispersion induced by discrete frailty

Lifetime Data Analysis - Frailty models are generally used to model heterogeneity between the individuals. The distribution of the frailty variable is often assumed to be continuous. However, there...     

Inference and Decision Making for 21st-Century Drug Development and Approval

ABSTRACT

The cost and time of pharmaceutical drug development continue to grow at rates that many say are unsustainable. These trends have enormous impact on what treatments get to patients, when they get them and how they are used. The statistical framework for supporting decisions in regulated clinical development of new medicines has followed a traditional path of frequentist methodology. Trials using hypothesis tests of “no treatment effect” are done routinely, and the p-value < 0.05 is often the determinant of what constitutes a “successful” trial. Many drugs fail in clinical development, adding to the cost of new medicines, and some evidence points blame at the deficiencies of the frequentist paradigm. An unknown number effective medicines may have been abandoned because trials were declared “unsuccessful” due to a p-value exceeding 0.05. Recently, the Bayesian paradigm has shown utility in the clinical drug development process for its probability-based inference. We argue for a Bayesian approach that employs data from other trials as a “prior” for Phase 3 trials so that synthesized evidence across trials can be utilized to compute probability statements that are valuable for understanding the magnitude of treatment effect. Such a Bayesian paradigm provides a promising framework for improving statistical inference and regulatory decision making.