Adult Sexual Outcomes of Child Sexual Abuse Vary According to Relationship Status

This study tested a moderation model in which the association between child sexual abuse severity and negative sexual outcomes (i.e., sexual avoidance and compulsivity) differed as a function of relationships status (i.e., single, cohabiting, and married individuals). A sample of 1,033 adults completed self‐report questionnaires online, and 21.5% reported childhood sexual abuse. Path analyses indicated that child sexual abuse severity was associated with higher sexual compulsivity in single individuals, both higher sexual avoidance and compulsivity in cohabiting individuals, and higher sexual avoidance in married individuals. The moderation model was invariant across men and women. These results suggest that the time course of negative sexual outcomes associated with child sexual abuse may follow distinct patterns of expression according to relationship status.     

Benefits and costs associated with mutual-help community-based recovery homes: The Oxford House model

We used data from a randomized controlled study of Oxford House (OH), a self-run, self-supporting recovery home, to conduct a cost-benefit analysis of the program. Following substance abuse treatment, individuals that were assigned to an OH condition (n = 68) were compared to individuals assigned to a usual care condition (n = 61). Economic cost measures were derived from length of stay at an Oxford House residence, and derived from self-reported measures of inpatient and outpatient treatment utilization. Economic benefit measures were derived from self-reported information on monthly income, days participating in illegal activities, binary responses of alcohol and drug use, and incarceration. Results suggest that OH compared quite favorably to usual care: the net benefit of an OH stay was estimated to be roughly $29,000 per person on average. Bootstrapped standard errors suggested that the net benefit was statistically significant. Costs were incrementally higher under OH, but the benefits in terms of reduced illegal activity, incarceration and substance use substantially outweighed the costs. The positive net benefit for Oxford House is primarily driven by a large difference in illegal activity between OH and usual care participants. Using sensitivity analyses, under more conservative assumptions we still arrived at a net benefit favorable to OH of $17,830 per person.     

Evaluation of an Intervention to Foster Time Perspective and Career Decidedness in a Group of Italian Adolescents

A structured 10‐didactic unit intervention was devised to foster adolescents’ time perspective and career decidedness. The study was conducted with 50 adolescents who were selected from a group of 624; 25 of the participants were randomly assigned to the control group and 25 were assigned to the experimental group. They were selected according to their level of career indecision and poor propensity to look to the future. A series of repeated measure analyses of variance were carried out to evaluate pre‐ and posttest differences between the experimental and control groups regarding time perspective and career decidedness. At posttest, the experimental group showed higher levels of continuity, hope, and career decidedness than did the control group. Implications for future practice and research are discussed.     

Estimating a sensitive proportion through randomized response procedures based on auxiliary information

Randomized response techniques are widely employed in surveys dealing with sensitive questions to ensure interviewee anonymity and reduce nonrespondents rates and biased responses. Since Warner’s (J Am Stat Assoc 60:63–69, 1965) pioneering work, many ingenious devices have been suggested to increase respondent’s privacy protection and to better estimate the proportion of people, π _A , bearing a sensitive attribute. In spite of the massive use of auxiliary information in the estimation of non-sensitive parameters, very few attempts have been made to improve randomization strategy performance when auxiliary variables are available. Moving from Zaizai’s (Model Assist Stat Appl 1:125–130, 2006) recent work, in this paper we provide a class of estimators for π _A , for a generic randomization scheme, when the mean of a supplementary non-sensitive variable is known. The minimum attainable variance bound of the class is obtained and the best estimator is also identified. We prove that the best estimator acts as a regression-type estimator which is at least as efficient as the corresponding estimator evaluated without allowing for the auxiliary variable. The general results are then applied to Warner and Simmons’ model.     

Realistic Major Previews in the School‐to‐College Transition of Italian High School Students

Industrial/organizational researchers have reported that realistic job previews diminish prospective workers' expectations but promote the satisfaction and persistence of those who ultimately accept a job assignment. The authors applied this strategy to the context of school‐to‐college transition; 354 Italian high school students were provided with a 2‐hour lecture designed to simulate exposure to a college major of their choice. Students showed moderate pre‐post increases in subject matter knowledge but reported small decreases in interests and outcome expectations (but not self‐efficacy) related to the academic major to which they were exposed.     

Inflated beta distributions

This paper considers the issue of modeling fractional data observed on [0,1), (0,1] or [0,1]. Mixed continuous-discrete distributions are proposed. The beta distribution is used to describe the continuous component of the model since its density can have quite different shapes depending on the values of the two parameters that index the distribution. Properties of the proposed distributions are examined. Also, estimation based on maximum likelihood and conditional moments is discussed. Finally, practical applications that employ real data are presented.     

Multivariate geostatistical mapping of radioactive contamination in the Maddalena Archipelago (Sardinia, Italy): spatial special issue

To improve the quality of prediction of radioactive contamination, geostatistical methods, and in particular multivariate geostatistical models, are increasingly being used. These methods, however, are optimal only in the case in which the data may be assumed Gaussian and do not properly cope with data measurements that are discrete, nonnegative or show some degree of skewness. To deal with these situations, here we consider a hierarchical model in which non-Gaussian variables of different kind are handled simultaneously. We show that when observations are assumed to be conditionally distributed as Poisson and Gamma, variograms and cross-variograms have convenient simple forms, and estimation of the parameters of the model can be carried out by Monte Carlo EM. This work was inspired by radioactive contamination data from the Maddalena Archipelago (Sardinia, Italy).     

Robustness of Parameter Estimation Procedures in Multilevel Models When Random Effects are MEP Distributed

In this paper we examine maximum likelihood estimation procedures in multilevel models for two level nesting structures. Usually, for fixed effects and variance components estimation, level-one error terms and random effects are assumed to be normally distributed. Nevertheless, in some circumstances this assumption might not be realistic, especially as concerns random effects. Thus we assume for random effects the family of multivariate exponential power distributions (MEP); subsequently, by means of Monte Carlo simulation procedures, we study robustness of maximum likelihood estimators under normal assumption when, actually, random effects are MEP distributed.