Empirical likelihood confidence intervals for the mean of a population containing many zero values

If a population contains many zero values and the sample size is not very large, the traditional normal approximation‐based confidence intervals for the population mean may have poor coverage probabilities. This problem is substantially reduced by constructing parametric likelihood ratio intervals when an appropriate mixture model can be found. In the context of survey sampling, however, there is a general preference for making minimal assumptions about the population under study. The authors have therefore investigated the coverage properties of nonparametric empirical likelihood confidence intervals for the population mean. They show that under a variety of hypothetical populations, these intervals often outperformed parametric likelihood intervals by having more balanced coverage rates and larger lower bounds. The authors illustrate their methodology using data from the Canadian Labour Force Survey for the year 2000.     

Parent‐Adolescent Communication About Sex: Retrospective Reports by Latino College Students

Latina female (n= 97) and Latino male (n= 69) college students (M age = 21.4 years) completed self‐report surveys regarding family of origin experiences, including sexual communication with parents while growing up. Latino parents of this comparatively highly educated sample tended to use direct rather than indirect strategies for communicating about sexuality with their children. Young women reported higher levels of sexual communication with mothers while growing up than did young men, and respondents reported less communication with fathers than mothers. Among young women, sexual communication with mother was positively associated with non‐Mexican origin and negatively associated with having older brothers living at home. In contrast, maternal education was positively associated with mother‐son communication about sex. Paternal education and the absence of older brothers positively predicted communication with both sons and daughters. The analyses provide novel information regarding sexual communication in Latino families and suggest directions for future research.     

A Bayesian method for classification and discrimination

We discuss Bayesian analyses of traditional normal-mixture models for classification and discrimination. The development involves application of an iterative resampling approach to Monte Carlo inference, commonly called Gibbs sampling, and demonstrates routine application. We stress the benefits of exact analyses over traditional classification and discrimination techniques, including the ease with which such analyses may be performed in a quite general setting, with possibly several normal-mixture components having different covariance matrices, the computation of exact posterior classification probabilities for observed data and for future cases to be classified, and posterior distributions for these probabilities that allow for assessment of second-level uncertainties in classification.     

Generating random variates from D-distributions via substitution sampling

Laud et al. (1993) describe a method for random variate generation from D-distributions. In this paper an alternative method using substitution sampling is given. An algorithm for the random variate generation from SD-distributions is also given.     

Marginal and association regression models for longitudinal binary data with drop‐outs: A likelihood‐based approach

Longitudinal data often contain missing observations, and it is in general difficult to justify particular missing data mechanisms, whether random or not, that may be hard to distinguish. The authors describe a likelihood‐based approach to estimating both the mean response and association parameters for longitudinal binary data with drop‐outs. They specify marginal and dependence structures as regression models which link the responses to the covariates. They illustrate their approach using a data set from the Waterloo Smoking Prevention Project They also report the results of simulation studies carried out to assess the performance of their technique under various circumstances.     

Potential exposures and risks from beryllium-containing products.

Beryllium is the strongest of the lightweight metals. Used primarily in military applications prior to the end of the Cold War, beryllium is finding new applications in many commercial products, including computers, telecommunication equipment, and consumer and automotive electronics. The use of beryllium in nondefense consumer applications is of concern because beryllium is toxic. Inhalation of beryllium dust or vapor causes a chronic lung disease in some individuals at concentrations as low as 0.01 microg/m3 in air. As beryllium enters wider commerce, it is prudent to ask what risks this might present to the general public and to workers downstream of the beryllium materials industry. We address this question by evaluating the potential for beryllium exposure from the manufacturing, use, recycle, and disposal of beryllium-containing products. Combining a market study with a qualitative exposure analysis, we determine which beryllium applications and life cycle phases have the largest exposure potential. Our analysis suggests that use and maintenance of the most common types of beryllium-containing products do not result in any obvious exposures of concern, and that maintenance activities result in greater exposures than product use. Product disposal has potential to present significant individual risks, but uncertainties concerning current and future routes of product disposal make it difficult to be definitive. Overall, additional exposure and dose-response data are needed to evaluate both the health significance of many exposure scenarios, and the adequacy of existing regulations to protect workers and the public. Although public exposures to beryllium and public awareness and concern regarding beryllium risks are currently low, beryllium risks have psychometric qualities that may lead to rapidly heightened public concern.     

Valuation of childhood risk reduction: the importance of age, risk preferences, and perspective.

This article explores two problems analysts face in determining how to estimate values for children's health and safety risk reductions. The first addresses the question: Do willingness‐to‐pay estimates for health risk changes differ across children and adults and, if so, how? To answer this question, the article first examines the potential effects of age and risk preferences on willingness to pay. A summary of the literature reporting empirical evidence of differences between willingness to pay for adult health and safety risk reductions and willingness to pay for health and safety risk reductions in children is also provided. The second dimension of the problem is a more fundamental issue: Whose perspective is relevant when valuing children's health effects—society's, children's, adults‐as‐children, or parents'? Each perspective is considered, followed ultimately by the conclusion that adopting a parental perspective through an intrahousehold allocation model seems closest to meeting the needs of the estimation problem at hand. A policy example in which the choice of perspective affects the outcome of a regulatory benefit‐cost analysis rounds out the article and emphasizes the importance of perspective.     

Uncertainty Analysis for Computer Model Projections of Hurricane Losses

Projecting losses associated with hurricanes is a complex and difficult undertaking that is wrought with uncertainties. Hurricane Charley, which struck southwest Florida on August 13, 2004, illustrates the uncertainty of forecasting damages from these storms. Due to shifts in the track and the rapid intensification of the storm, real-time estimates grew from 2 to 3 billion dollars in losses late on August 12 to a peak of 50 billion dollars for a brief time as the storm appeared to be headed for the Tampa Bay area. The storm hit the resort areas of Charlotte Harbor near Punta Gorda and then went on to Orlando in the central part of the state, with early poststorm estimates converging on a damage estimate in the 28 to 31 billion dollars range. Comparable damage to central Florida had not been seen since Hurricane Donna in 1960. The Florida Commission on Hurricane Loss Projection Methodology (FCHLPM) has recognized the role of computer models in projecting losses from hurricanes. The FCHLPM established a professional team to perform onsite (confidential) audits of computer models developed by several different companies in the United States that seek to have their models approved for use in insurance rate filings in Florida. The team's members represent the fields of actuarial science, computer science, meteorology, statistics, and wind and structural engineering. An important part of the auditing process requires uncertainty and sensitivity analyses to be performed with the applicant's proprietary model. To influence future such analyses, an uncertainty and sensitivity analysis has been completed for loss projections arising from use of a Holland B parameter hurricane wind field model. Uncertainty analysis quantifies the expected percentage reduction in the uncertainty of wind speed and loss that is attributable to each of the input variables.     

The Experience of Gender Change in Public Sector Organizations

The state has a twofold relationship to gender change in society, through its overall steering capacity and through the gendered character of its constituent agencies. It is therefore important to understand the experience of gender change in state organizations. The findings from a study of gender relations in ten public‐sector worksites in New South Wales, Australia are presented. There is a widespread consciousness of gender change linked with new labour processes, restructuring and new patterns of management. These changes are uneven and limits to change are visible. Gender is recognized as an organizational problem in specific circumstances, most visibly where men’s resistance to change appears. A number of mechanisms limit the consciousness of gender as a problem. Several trends, including the current strength of neo‐liberalism, converge to make the gender‐neutral workplace the principal goal of gender reform in the public‐sector workplace. This, however, limits the state’s steering capacity in regard to societal gender relations.