New tests for stochastic order with application to case control studies

It is shown that if a binary regression function is increasing then retrospective sampling induces a stochastic ordering of the covariate distributions among the responders, which we call cases, and the non-responders, which we call controls. We also show that if the covariate distributions are stochastically ordered then the regression function must be increasing. This means that testing whether the regression function is monotone is equivalent to testing whether the covariate distributions are stochastically ordered. Capitalizing on these new probabilistic observations we proceed to develop two new non-parametric tests for stochastic order. The new tests are based on either the maximally selected, or integrated, chi-bar statistic of order one. The tests are easy to compute and interpret and their large sampling distributions are easily found. Numerical comparisons show that they compare favorably with existing methods in both small and large samples. We emphasize that the new tests are applicable to any testing problem involving two stochastically ordered distributions.     

Exclusion of HIV-positive people with disabilities in the media

This current issue piece aims to address the harmful exclusion of people with disabilities in the Iranian media. In a case study, this author collected news related to statistics of HIV-positive people covered by popular news websites written in the Persian language between June 2011 and June 2012. Within the analysed electronic texts, no reference was made to the number of HIV-positive people with disabilities. Under the rubric of critical discourse analysis, one can argue that this lack of representation may also be linked to a more general level of discourse that constitutes the marginalization of people with disabilities. This damaging exclusion both legitimizes and reproduces the ideology that people with disabilities are social minorities who can be excluded to the benefit of powerful people. This current issue piece also discusses the potential negative consequences of excluding HIV-positive people with disabilities from the discourse of HIV/AIDS in the media. Ultimately, the conceivable reasons for the Iranian government failure or refusal to publish the statistics of HIV-positive people with disabilities will be provided. Studies from various countries could shed more light on the exclusion of HIV-positive people with disabilities in the media and the interplay between HIV/AIDS and disability issues.     

Evaluation of corporate governance systems by credit rating agencies

In periods of high market volatility, and in order to minimize their risks, some investors prefer to invest their funds in well-governed companies. This paper aims to describe the methodology used by rating agencies to assess corporate governance systems (CGS) and to compare agencies’ practices. More and more the shareholders and creditors incorporate mechanisms related to CGS in the assessment of risks. Using a sample of five rating agencies, we distill 51 governance criteria to two governance factors using principal components analysis. The first factor represents the “shareholders rights and board of directors”. The second one is related to “remuneration policy and convergence of interests for shareholders and managers”. We identify three different business models for the corporate governance rating process.     

A two-step robust estimation of the process mean using M-estimator

Parameter estimation is the first step in constructing control charts. One of these parameters is the process mean. The classical estimators of the process mean are sensitive to the presence of outlying data and subgroups which contaminate the whole data. In existing robust estimators for the process mean, the effects of the presence of the individual outliers are being considered, while, in this paper, a robust estimator is being proposed to reduce the effect of outlying subgroups as well as the individual outliers within a subgroup. The proposed estimator was compared with some classical and robust estimators of the process mean. Although, its relative efficiency is fourth among the estimators tested, its robustness and efficiency are large when the outlying subgroups are present. Evaluation of the results indicated that the proposed estimator is less sensitive to the presence of outliers and the process mean performs well when there are no individual outliers or outlying subgroups.     

What Explains the 2007–2009 Drop in Employment?

We show that deterioration in household balance sheets, or the housing net worth channel, played a significant role in the sharp decline in U.S. employment between 2007 and 2009. Counties with a larger decline in housing net worth experience a larger decline in non‐tradable employment. This result is not driven by industry‐specific supply‐side shocks, exposure to the construction sector, policy‐induced business uncertainty, or contemporaneous credit supply tightening. We find little evidence of labor market adjustment in response to the housing net worth shock. There is no significant expansion of the tradable sector in counties with the largest decline in housing net worth. Further, there is little evidence of wage adjustment within or emigration out of the hardest hit counties.     

The Siting of Radioactive Waste Faculties: What Are the Effects on Communities?1

Abstract Despite literally dozens of attempts, and the expenditure of billions of dollars, efforts to site radioactive waste disposal facilities in this country have been uniformly unsuccessful. While both researchers and policymakers continue to address reasons for these failures, little attention is being given to the consequences for the communities themselves of these intensive siting battles. Using a research framework that addresses both the sources and consequences of community conflict, we examine what is happening in four different areas currently being considered as potential hosts for either a high- or a low-level radioactive waste facility. Some degree of conflict is observed in each community, although it varies from one area to another based on such differences as potential to experience economic benefits, perceptions of class and ethnic equity, and the role of extra-local players in the controversy. We conclude that current policies lead to inequitable distributions of risk that, in turn, create “fairness” questions that are important both in explaining current patterns of conflict and in anticipating long-term consequences for the affected communities.     

Bayesian analysis of covariance under inverse Gaussian model

This paper considers the problem of analysis of covariance (ANCOVA) under the assumption of inverse Gaussian distribution for response variable from the Bayesian point of view. We develop a fully Bayesian model for ANCOVA based on the conjugate prior distributions for parameters contained in the model. The Bayes estimator of parameters, ANCOVA model and adjusted effects for both treatments and covariates along with predictive distribution of future observations are developed. We also provide the essentials for comparing adjusted treatments effects and adjusted factor effects. A simulation study and a real world application are also performed to illustrate and evaluate the proposed Bayesian model.     

Inferences on stress–strength parameter based on GLD5 distribution

Let X and Y be independent random variables distributed as generalized Lindley distribution type 5 (GLD5). This article deals with the estimation of the stress–strength parameter R = P(Y < X), which plays an important role in reliability analysis. For this purpose, the maximum likelihood and the uniformly minimum variance unbiased estimators are presented in the explicit form. Moreover, considering Arnold and Strauss’ bivariate Gamma distribution as an informative prior and Jeffreys’ as noninformative prior, the Bayes estimators are derived. Various bootstrap confidence intervals are also proposed and, finally, the presented methods are compared using a simulation study.     

Necessary and sufficient conditions for stochastic orders between (n − r + 1)-out-of-n systems in proportional hazard (reversed hazard) rates model

Consider two (n ? r + 1)-out-of-n systems, one with independent and non-identically distributed components and another with independent and identically distributed components. When the lifetimes of components follow the proportional hazard rates model, we establish a necessary and sufficient condition for the usual stochastic order to hold between the lifetimes of these two systems. For the special case of r = 2, some generalized forms of this result to the hazard rate, dispersive and likelihood ratio orders are also obtained. Moreover, for the case when the lifetimes of components follow the proportional reversed hazard rates model, we derive some similar results for comparing the lifetimes of two systems . Applications of the established results to different situations are finally illustrated.