A Comparison of Estimation Methods on the Coverage Probability of Satterthwaite Confidence Intervals for Assay Precision with Unbalanced Data

Construction of closed-form confidence intervals on linear combinations of variance components were developed generically for balanced data and studied mainly for one-way and two-way random effects analysis of variance models. The Satterthwaite approach is easily generalized to unbalanced data and modified to increase its coverage probability. They are applied on measures of assay precision in combination with (restricted) maximum likelihood and Henderson III Type 1 and 3 estimation. Simulations of interlaboratory studies with unbalanced data and with small sample sizes do not show superiority of any of the possible combinations of estimation methods and Satterthwaite approaches on three measures of assay precision. However, the modified Satterthwaite approach with Henderson III Type 3 estimation is often preferred above the other combinations.     

The Power Series Cure Rate Model: An Application to a Cutaneous Melanoma Data

In this article we propose a new cure rate survival model. In our approach the number of competing causes of the event of interest is assumed to follow an exponential discrete power series distribution. An advantage of our model is that it is very flexible, including several particular cases, such as, Bernoulli, geometric, Poisson, etc. Moreover, we derive the appropriate matrices for assessing local influence on the parameter estimates under different perturbation schemes and present some ways to perform global influence analysis. Distribution fitting can be tested for the best fitting in a straightforward way. Maximum likelihood estimation is discussed. Our proposed model is illustrated through cutaneous melanoma data.     

General mathematical properties,regression and applications of the log-gamma-generated family

The construction of some wider families of continuous distributions obtained recently has attracted applied statisticians due to the analytical facilities available for easy computation of special functions in programming software. We study some general mathematical properties of the log-gamma-generated (LGG) family defined by Amini, MirMostafaee, and Ahmadi (2014 Amini, M., S. M. T. K. MirMostafaee, and J. Ahmadi. 2014. Log-gamma-generated families of distributions. Statistics 48:913–32.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]). It generalizes the gamma-generated class pioneered by Risti? and Balakrishnan (2012 Risti?, M. M., and N. Balakrishnan. 2012. The gamma exponentiated exponential distribution. Journal of Statistical Computation and Simulation 82:1191–206.[Taylor &; Francis Online], [Web of Science ®] , [Google Scholar]). We present some of its special models and derive explicit expressions for the ordinary and incomplete moments, generating and quantile functions, mean deviations, Bonferroni and Lorenz curves, Shannon entropy, Rényi entropy, reliability, and order statistics. Models in this family are compared with nested and non nested models. Further, we propose and study a new LGG family regression model. We demonstrate that the new regression model can be applied to censored data since it represents a parametric family of models and therefore can be used more effectively in the analysis of survival data. We prove that the proposed models can provide consistently better fits in some applications to real data sets.     

The Kumaraswamy Gumbel distribution

The Gumbel distribution is perhaps the most widely applied statistical distribution for problems in engineering. We propose a generalization—referred to as the Kumaraswamy Gumbel distribution—and provide a comprehensive treatment of its structural properties. We obtain the analytical shapes of the density and hazard rate functions. We calculate explicit expressions for the moments and generating function. The variation of the skewness and kurtosis measures is examined and the asymptotic distribution of the extreme values is investigated. Explicit expressions are also derived for the moments of order statistics. The methods of maximum likelihood and parametric bootstrap and a Bayesian procedure are proposed for estimating the model parameters. We obtain the expected information matrix. An application of the new model to a real dataset illustrates the potentiality of the proposed model. Two bivariate generalizations of the model are proposed.     

A bivariate regression model for matched paired survival data: local influence and residual analysis

The use of bivariate distributions plays a fundamental role in survival and reliability studies. In this paper, we consider a location scale model for bivariate survival times based on the proposal of a copula to model the dependence of bivariate survival data. For the proposed model, we consider inferential procedures based on maximum likelihood. Gains in efficiency from bivariate models are also examined in the censored data setting. For different parameter settings, sample sizes and censoring percentages, various simulation studies are performed and compared to the performance of the bivariate regression model for matched paired survival data. Sensitivity analysis methods such as local and total influence are presented and derived under three perturbation schemes. The martingale marginal and the deviance marginal residual measures are used to check the adequacy of the model. Furthermore, we propose a new measure which we call modified deviance component residual. The methodology in the paper is illustrated on a lifetime data set for kidney patients.     

Estimation and diagnostics for heteroscedastic nonlinear regression models based on scale mixtures of skew-normal distributions

An extension of some standard likelihood based procedures to heteroscedastic nonlinear regression models under scale mixtures of skew-normal (SMSN) distributions is developed. This novel class of models provides a useful generalization of the heteroscedastic symmetrical nonlinear regression models (Cysneiros et al., 2010), since the random term distributions cover both symmetric as well as asymmetric and heavy-tailed distributions such as skew-t, skew-slash, skew-contaminated normal, among others. A simple EM-type algorithm for iteratively computing maximum likelihood estimates of the parameters is presented and the observed information matrix is derived analytically. In order to examine the performance of the proposed methods, some simulation studies are presented to show the robust aspect of this flexible class against outlying and influential observations and that the maximum likelihood estimates based on the EM-type algorithm do provide good asymptotic properties. Furthermore, local influence measures and the one-step approximations of the estimates in the case-deletion model are obtained. Finally, an illustration of the methodology is given considering a data set previously analyzed under the homoscedastic skew-t nonlinear regression model.     

Recipes for Attention: Policy Reforms,Crises, Organizational Characteristics,and the Newspaper Coverage of the LGBT Movement, 1969–2009

Why do some organizations in a movement seeking social change gain extensive national newspaper coverage? To address the question, we innovate in theoretical and empirical ways. First, we elaborate a theoretical argument that builds from the political mediation theory of movement consequences and incorporates the social organization of newspaper practices. This media and political mediation model integrates political and media contexts and organizations' characteristics and actions. With this model, we hypothesize two main routes to coverage: one that includes changes in public policy and involves policy‐engaged, well‐resourced, and inclusive organizations and a second that combines social crises and protest organizations. Second, we appraise these arguments with the first analysis of the national coverage of all organizations in a social movement over its career: 84 lesbian, gay, bisexual, and transgender rights and AIDS‐related organizations in the New York Times, Los Angeles Times, and Wall Street Journal from 1969 to 2010. These analyses go beyond previous research that provides either snapshots of many organizations at one point in time or overtime analyses of aggregated groups of organizations or individual organizations. The results of both historical and fuzzy set qualitative comparative analyses support our media and political mediation model.     

‘Dirt,Death and Danger? I Don't Recall Any Adverse Reaction …’: Masculinity and the Taint Management of Hospital Private Security Work

Drawing on an ethnographic narrative written by one of the authors following his resignation from a hospital private security team in Ottawa, Canada and interview data gleaned from eight security men (all former colleagues), this article explores how hospital private security officers draw on discourses of masculinity to navigate the ‘dirty’ boundaries of their work, and to preserve their alpha‐guard statuses as controlled, autonomous and authoritative subjects. We found that hospital guards manage and deflect taint status by emphasizing their resiliency, emotional detachment and enthusiasm towards morbid, disturbing and dangerous tasks. Guards who seek to challenge these components of the job may be subject to gender harassment and reprisal from other guards, senior security officials and nursing staff. Overall, these narratives call attention to the necessity of hospital training programmes, de‐briefing exercises and best‐communication practices that promote the physical and emotional well‐being of persons who engage in intensive forms of dirty work.     

From bias to coverage: What explains how news organizations treat social movements

Why do newspapers cover social movement actors, and why is this coverage sometimes favorable? Early scholarship saw the news media mainly as a source of data on collective action, and sought to ascertain its biases, but scholarship has increasingly focused directly on why movements gain coverage, especially coverage that can advance their goals. To understand why and how newspapers cover movement actors, we start with the insight that movements rely on the news media for many reasons, but their coverage is largely in the control of news institutions. In this review, we focus on perspectives that specify 3‐way interactions between the characteristics of newspapers, social movement actors, and the social and political contexts, but we begin with how news media institutions are organized. We conclude with suggestions for future research that take advantage of the digital revolution of the last generation.     

PARENTAL CHOICE OF SCHOOL CHARACTERISTICS: ESTIMATION USING STATE-WIDE DATA

This article attempts to proxy parental alienation from public schools across states in order to obtain measures of quality dispersion and of the educational characteristics to which families are most sensitive. The indicator of alienation is the choice of private schooling. Since the likelihood of such choice is known from published enrollment ratios, the task is to explain why they vary so widely across states. Of the newer hypotheses tested, that of teacher strike records is strongly significant and in the expected direction. Other novel findings concern the share of administration, teacher memberships of the National Education Association and the proportion of whites to nonwhites in the population.