Slice sampling for simulation based fitting of spatial data models

An auxiliary variable method based on a slice sampler is shown to provide an attractive simulation-based model fitting strategy for fitting Bayesian models under proper priors. Though broadly applicable, we illustrate in the context of fitting spatial models for geo-referenced or point source data. Spatial modeling within a Bayesian framework offers inferential advantages and the slice sampler provides an algorithm which is essentially off the shelf. Further potential advantages over importance sampling approaches and Metropolis approaches are noted and illustrative examples are supplied.     

Enriching Research on Marital Enrichment Programs

The existing empirical literature on the outcomes of marital and pre-marital enrichment programs is critically reviewed. While the majority of studies have used untreated control groups and appear to offer very striking evidence of meaningful change as a result of these enrichment experiences, several important methodological deficiencies are common to these investigations and, therefore, require a cautious optimism about the efficacy of these programs. Six specific issues are addressed in an effort to improve the quality and utility of further research and practice in this area.     

Philanthropic styles

The challenge of resource development, particularly among major donors, has led nonprofits to adopt marketing techniques, including market segmentation. The benefit segmentation approach used in this study of the giving motivations of 218 major donors reveals seven philanthropic styles: (1) Communitarians, (2) the Devout, (3) Investors, (4) Socialites, (5) Repayers, (6) Altruists, and (7) Dynasts. Examples of how knowledge of philanthropic styles can aid in nonprofit resource development are provided.     

The office of scientific integrity investigations: The importance of data analysis

Certified Public Accountants serve as independent auditors of financial statements. They perform information‐integrity testing for the economy and society, adding creditability to financial statements prepared by organizations’ management. Investors, creditors, and others rely on these financial statements and the audit report to make business decisions. Auditing work involves gathering evidence (research) and forming an opinion (reporting results) about the “fairness”; of financial statements according to regulatory, legal, and professional rules. As researchers, auditors are subject to a complex network of mechanisms to promote accountability in their work. These mechanisms exist at environmental, professional, and audit‐firm levels. They combine to influence the judgments of individual auditors.     

The personal protective behaviors of college student drinkers: evidence of indigenous protective norms

Given the prevalence of alcohol consumption and the relative infrequency of harm among college students, the authors sought to determine how most college students protect themselves from alcohol-related harm. An analysis of the aggregate National College Health Assessment data identified a cluster of personal protective behaviors that correlated with reduced risk when drinking. Further analysis revealed that nearly three-quarters of student drinkers regularly employ at least 1 protective behavior, and well over half of the students who use protective behaviors routinely employ 2 or more. In addition, the data reveal that student drinkers employ situational abstinence, with nearly 7 out of 10 students reporting that they sometimes or usually refrain from drinking alcohol when they socialize. The use of these protective behaviors is a strong predictor of safety and harm for college-student drinkers.     

An Investigation of Quantile Function Estimators Relative to Quantile Confidence Interval Coverage

In this article, we investigate the limitations of traditional quantile function estimators and introduce a new class of quantile function estimators, namely, the semi-parametric tail-extrapolated quantile estimators, which has excellent performance for estimating the extreme tails with finite sample sizes. The smoothed bootstrap and direct density estimation via the characteristic function methods are developed for the estimation of confidence intervals. Through a comprehensive simulation study to compare the confidence interval estimations of various quantile estimators, we discuss the preferred quantile estimator in conjunction with the confidence interval estimation method to use under different circumstances. Data examples are given to illustrate the superiority of the semi-parametric tail-extrapolated quantile estimators. The new class of quantile estimators is obtained by slight modification of traditional quantile estimators, and therefore, should be specifically appealing to researchers in estimating the extreme tails.     

Estimation of functions of the parameters of a normal distribution

Several authors have considered the problem of estimating parameters of a distribution after some fixed Gaussian inducing transformation has been applied to the observations. This paper extends this work to the situation where the observations represent a noisy version of a true process, the parameters of the latter requiring estimation