Confidence Intervals for the Median of a Finite Population Based on the Sign Test

This article presents methods for constructing confidence intervals for the median of a finite population under simple random sampling without replacement, stratified random sampling, and cluster sampling. The confidence intervals, as well as point estimates and test statistics, are derived from sign estimating functions which are based on the well-known sign test. Therefore, a unified approach for inference about the median of a finite population is given.     

A network ridesharing experiment with sequential choice of transportation mode

Within the last decade, there has been a dramatic bloom in ridesharing businesses along with the emergence of new enabling technologies. A central issue in ridesharing, which is also important in the general domain of cost-sharing in economics and computer science, is that the sharing of cost implies positive externalities and hence coordination problems for the network users. We investigate these problems experimentally in the present study. In particular, we focus on how sequential observability of transportation mode choices can be a powerful facilitator of coordination in ridesharing. Our study abstracts the essential issues of coordination in ridesharing into a directed network game with experimentally testable predictions. In line with the theoretical analysis, our experimental evidence shows that even a limited extent of sequential choice observability might lead to efficient coordination. However, convergence to efficiency is slower with more limited observability, resulting in a significant increase in travel cost.     

Metamodeling of aircraft infrared signature dispersion

Existing computer simulations of aircraft InfraRed Signature (IRS) do not account for the dispersion induced by uncertainty on input data such as aircraft aspect angles and meteorological conditions. As a result, they are of little use to estimate the detection performance of optronic systems: in that case, the scenario encompasses a lot of possible situations that must indeed be addressed, but cannot be singly simulated. In this paper, a three-step methodological approach for predicting simulated IRS dispersion of imperfectly known aircraft is proposed. The first step is a sensitivity analysis. The second step consists in a Quasi-Monte Carlo survey of the code output dispersion. In the last step, a neural network metamodel of the IRS simulation code is constructed. It will allow carrying out thorough computationally demanding tasks, such as those required for optimization of an optronic sensor. This method is illustrated in a typical scenario, namely an air-to-ground full-frontal attack by a generic combat aircraft, and gives satisfactory estimation of the infrared signature dispersion.     

A computational understanding of partial and part determination coefficients

A computational understanding of partial and part determination coefficients brings additional insight concerning their interpretations in regression. It also enables one to easily identify synergistic combinations. Benefits from the practical interpretation of synergism have yet to be fully explored and exploited. Hence, this study provides a new dimension in the analysis of data.     

Systematic Review of Motives for Episodic Volunteering

Although episodic volunteers are a critical resource for many organisations, their motives for volunteering are poorly understood. A systematic review was conducted to describe empirical evidence about motives for episodic volunteering (EV) across sectors (sport, tourism, events, health and social welfare). Identified EV motives were then categorised using core functions from the Volunteer Functions Inventory (VFI) for comparison across studies. Twelve databases (1990–December 2014) were searched. Thirty-three English language studies included results describing EV motives. Studies were predominantly cross-sectional, quantitative, event-based and originating in North America. Measurement of motives was also inconsistent. Common motives were helping others and socialising. Physical challenge and healing motives were specific to sport-based events and charity sport events, respectively. Over 80 % of motives were classified using VFI functions, particularly enhancement, values and social functions. The VFI supplemented by qualitative work may be efficacious to further identify EV motives and retention strategies.     

Attachment‐Based Family Therapy With a 13‐Year‐Old Girl Presenting With High Risk for Suicide

This article describes the application of Attachment‐Based Family Therapy (ABFT) to the treatment of a 13‐year‐old female adolescent presenting with high risk of suicide, complicated by a history of depression and sexual trauma. The article begins with an overview of ABFT, including (a) how attachment theory guides treatment; (b) the structure of the clinical model; and (c) the data that provide empirical support. A case example is then presented that exemplifies the primary clinical procedures used to reach therapeutic goals in ABFT, including attachment repair and autonomy/competence promotion. Weekly changes in suicide ideation and depression scores are presented. The article concludes with a discussion about implications for family‐based treatment of suicidal youth.