Second-order properties of intraclass correlation estimators for a symmetric normal distribution

Consider the problem of estimating the intraclass correlation coefficient of a symmetric normal distribution under the squared error loss function. The general admissibility of the standard estimators of the intraclass correlation coefficient is hard to check due to their complicated sampling distributions. We follow the asymptotic decision-theoretic approach of Ghosh and Sinha (1981) and prove that the three standard intraclass correlation estimators (the maximum-likelihood estimator, the method-of-moments estimator and the first-order unbiased estimator) are second-order admissible for all p ≥ 2, p being the dimension of the distribution.     

Bayesian variable selection with strong heredity constraints

In this paper, we propose a Bayesian variable selection method for linear regression models with high-order interactions. Our method automatically enforces the heredity constraint, that is, a higher order interaction term can exist in the model only if both of its parent terms are in the model. Based on the stochastic search variable selection George and McCulloch (1993), we propose a novel hierarchical prior that fully considers the heredity constraint and controls the degree of sparsity simultaneously. We develop a Markov chain Monte Carlo (MCMC) algorithm to explore the model space efficiently while accounting for the heredity constraint by modifying the shotgun stochastic search algorithm Hans et al. (2007). The performance of the new model is demonstrated through comparisons with other methods. Numerical studies on both real data analysis and simulations show that our new method tends to find relevant variable more effectively when higher order interaction terms are considered.     

A note on the optimal number of centre runs in a second phase design of response surface methods

In searching for optimum conditions, the response surface methods comprise two phases. In the first phase, the method of the steepest ascent with a 2 k-p design is used in searching for a region of improved response. The curvature of the response surface is checked in the second phase. For testing the evidence of curvature, a reasonable design is a 2 k-p fractional factorial design augmented by centre runs. Using c-optimality criterion, the optimal number of centre runs is investigated. Incorporating c-efficiencies for the curvature test with D-efficiencies and G-efficiencies of CCDs for the quadratic response surfaces and then, adopting the Mini-Max principle, i.e. maximizing the worst efficiency, we propose robust centre runs with respect to the three optimality criteria to be chosen.     

Order test for high-dimensional two-sample means

We propose a new method to test the order between two high-dimensional mean curves. The new statistic extends the approach of Follmann (1996) to high-dimensional data by adapting the strategy of Bai and Saranadasa (1996). The proposed procedure is an alternative to the non-negative basis matrix factorization (NBMF) based test of Lee et al. (2008) for the same hypothesis, but it is much easier to implement. We derive the asymptotic mean and variance of the proposed test statistic under the null hypothesis of equal mean curves. Based on theoretical results, we put forward a permutation procedure to approximate the null distribution of the new test statistic. We compare the power of the proposed test with that of the NBMF-based test via simulations. We illustrate the approach by an application to tidal volume traces.     

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.     

Estimates of trade-related adjustment costs in Syria

The scope and complexity of international trading arrangements in the Middle East, as well as their spotty historical record of success, underscore the urgent need for an adequate understanding of the relative costs and benefits of participation in preferential trading arrangements and, more generally, of changes in the domestic import regimes. This paper seeks to address this problem by providing estimates of the adjustment costs associated with two broad classes of hypothetical trade policy scenarios for Syria: participation in the proposed EU-Syria Association Agreement, and border tax-related changes affecting the domestic import regime. We find that the revenue consequences of the first scenario are likely to be low if an appropriate stepwise implementation of the agreement can be ensured; our analysis of the second scenario suggests that all border taxes can be eliminated, and the number of tariff bands reduced, while ensuring revenue neutrality, if a VAT of a reasonable size is introduced.