On asymptotic optimality of bayes empirical bayes estimators

In an empirical Bayes decision problem, a prior distribution ? is placed on a one-dimensfonal family G of priors G_w, wεΩ, to produce a Bayes empirical Bayes estimator, The asymptotic optimaiity of the Bayes estimator is established when the support of ? is Ω and the marginal distributions H_w have monotone likelihood ratio and continuous Kullback-Leibler information number.     

Optimal stopping for Brownian motion with applications to sequential analysis and option pricing

Herman Chernoff made fundamental contributions to analytical and computational methods for solving optimal stopping problems for Brownian motion. He also showed how these optimal stopping problems are closely related to some basic problems in sequential analysis and singular stochastic control. This paper gives a survey of these and related developments and describes some recent applications to option valuation in financial economics.     

Cross‐Cultural Consistency of the Demand/Withdraw Interaction Pattern in Couples

In order to examine the cross‐cultural consistency of several patterns of couple communication, 363 participants from four different countries (Brazil, Italy, Taiwan, and the United States) completed self‐report measures about communication and satisfaction in their romantic relationships. Across countries, constructive communication was positively associated with relationship satisfaction, whereas demand/withdraw communication was negatively associated with relationship satisfaction. Woman demand/man withdraw communication was significantly more likely than man demand/woman withdraw communication. Also, some evidence suggested women wanted greater closeness versus independence in their relationships than did men. Differences between partners in desire for closeness versus independence were associated with greater demand/withdraw communication. The possible bases for the demand/withdraw pattern of communication and its gender linkage are discussed.     

Experiences of trafficked and sexually exploited boys transitioning from shelter programmes into the community: Findings from a longitudinal study

This article explores the perspectives of Cambodian boys who have experienced human trafficking and sexual exploitation on their experiences transitioning out of shelters and re‐entering the community. We used an interpretive phenomenological approach to analyse 81 interviews and narrative summaries of interviews drawn from Chab Dai's 10‐year longitudinal study with survivors in Cambodia (n = 22). Themes included: minimal involvement in planning for re/integration; conflicted feelings about life in the community; challenges completing school and securing employment; importance of community‐based services; unfulfilled expectations; violence in the community; and a desire to return to the shelter.     

Using ranked set sampling with binary outcomes in cluster randomized designs

We study the use of ranked set sampling (RSS) with binary outcomes in cluster-randomized designs (CRDs), where a generalized linear mixed model (GLMM) is used to model the hierarchical data structure involved. Under the GLMM-based framework, we propose three different approaches to estimate the treatment effect, including the nonparametric (NP), maximum likelihood (ML) and pseudo likelihood (PL) estimators. We investigate their asymptotic properties and examine their finite-sample performance via simulation. Based on these three RSS estimators, we further develop procedures for testing the existence of the treatment effect. We examine the power and size of our proposed RSS tests and compare them with existing tests based on simple random sampling (SRS). All the proposed RSS estimation and test methods are illustrated with two data examples, one for rare events and the other for non-extreme events. Throughout our investigations, we also consider the possible effect of imperfect ranking. Among the proposed methods, we provide recommendations on whether to use RSS rather than SRS with binary outcomes in CRDs and, if yes, when to use which RSS method. The Canadian Journal of Statistics 48: 342–365; 2020 © 2019 Statistical Society of Canada     

A GEE approach to estimating accuracy and its confidence intervals for correlated data

In this paper, we provide a method for constructing confidence interval for accuracy in correlated observations, where one sample of patients is being rated by two or more diagnostic tests. Confidence intervals for other measures of diagnostic tests, such as sensitivity, specificity, positive predictive value, and negative predictive value, have already been developed for clustered or correlated observations using the generalized estimating equations (GEE) method. Here, we use the GEE and delta‐method to construct confidence intervals for accuracy, the proportion of patients who are correctly classified. Simulation results verify that the estimated confidence intervals exhibit consistent/appropriate coverage rates.     

Avoiding Covid-19 risk information in the United States: The role of attitudes,norms, affect,social dominance orientations,and perceived trustworthiness of scientists

This study seeks guidance from the planned risk information avoidance model to explore drivers of risk information avoidance in the context of COVID-19. Data were collected early during the pandemic. Among our most notable results is that participants who are more oriented toward social dominance and are more skeptical of scientists’ credibility have (1) more supportive attitudes toward risk information avoidance and (2) feel social pressure to avoid risk information. The findings of this study highlight how the role of skepticism in science and intergroup ideologies, such as social dominance, can have important implications for how people learn about health-related information, even in times of heightened crisis.     

Scheduling of raw-material unloading from ships at a steelworks

Formulating a schedule for unloading raw material from ships at the seaport of a steelworks is a difficult task. Even in its simplest possible form, finding an optimum solution for the problem is nondeterministic polynomial time (NP)-hard. The problem at a steelworks gets more complicated due to several factors, such as the difference in capacities of unloading equipment, the requirement of keeping ships balanced and the dynamic nature of berthing eligibility of each ship, as governed by the weight of the remaining payload. Moreover, the raw material must be transported through a network of belt conveyor units to designated storage yards while being discharged from ships. The combinatorial nature of this belt conveyor operation is analysed in this article. A heuristic approach to the raw-material unloading problem is proposed and its effectiveness was tested with real-world examples.     

Urban E-Government Initiatives and Environmental Decision Performance in Korea

Although e-government initiatives have been credited as enginesof government reform, empirical evidence is insufficient todetermine their effects on public sector performance. To explorethe impact of e-government on local governance, this articleexamines how e-government initiatives influence the perceivedperformance of environmental decision making in an urban contextand what organizational and contextual factors affect Web-aideddecision performance. Data were collected from the content analysisof city government Web sites and a nationwide survey of cityofficials in Korea. Findings from path analysis show that (1)information technology leadership of senior management and Website quality are key to decision intelligence, quality, andspeed and (2) e-government Web divide, a gap in the capabilityof city Web sites to support public service delivery and democraticinteraction, translates into disparities in environmental decisionperformance across cities. Additionally, environmental activismis a significant factor shaping the impact of e-government onenvironmental decision making. E-government initiatives contributeto local governance performance, but their impacts vary, dependingon Web site quality and the entrepreneurial leadership of publicmanagers.     

A Model for Measuring Supplier Risk: Do Operational Capability Indicators Enhance the Prediction Accuracy of Supplier Risk?

The purpose of this study was to develop a supplier risk assessment model for buyers to estimate supplier risk. It is one of the few empirical studies that considers both operational capability indicators and financial indicators; a standard logit model with five key variables (switching cost, operating profit margin, asset turnover ratio, quality capability and technological capability) was suggested as a practical tool. This model not only enhanced the accuracy of supplier risk assessment, but also served as a core element of a new supply chain management tool, ‘supplier management at risk’. More practically, the model enables purchasing firms to assess supplier risk and take proactive measures against the estimated risk.