Older women's fears of violence: the need for interventions that enable active ageing

Women's fear of violence can impact negatively on their active participation in life. An ageing survey conducted with 2,620 Australian respondents aged 50 to 90 years examined aspects of work, learning, social, spiritual and emotional status, health, vision, home, life events, demographics, and asked an open-ended question about what being actively engaged in life meant. Ordinal regression was carried out on two dependent variables: wanting and needing to learn to discourage violence. Analyses found that as women's age increased, those on lower incomes were more likely than others to say they needed to learn how to discourage violence against them. This paper investigates the variables associated with the findings-transport, finances, news media, home safety, and reduced social interactions. Results highlight the importance of understanding women's fear in the context of personal and social issues, and the need to provide learning opportunities to improve safety and social engagement.     

Comment on “compromised birth outcomes and infant mortality among racial and ethnic groups”

Frisbie, Forbes, and Pullum (1996) show that it is meaningful to account for low birth weight, preterm delivery, and intrauterine growth-retardation when analyzing differences in compromised birth outcomes and infant mortality among racial and ethnic groups. I compare their findings for the 1987 U.S. birth cohort with findings for the 1988 U.S. birth cohort, using linked birth and infant death vital statistics from the National Center for Health Statistics. I focus on their calculation of fetal growth curves, which are highly at odds with the curves commonly used in the obstetric and pediatric literature. I compare birth outcome distributions and infant death probabilities using Frisbie et al. 's method and other standards. I conclude that Frisbie et al. 's method is not suited for the study of intrauterine growth-retardation at the population level because of the major flaws in gestational age measurement that exist in the type of data they use. An appropriate alternative is to apply a standard of normal intrauterine growth derived from antenatal estimation of fetal weight-for-gestational-age to the vital statistics data.     

Peer Group Affiliation of Children: The Role of Perceived Popularity,Likeability, and Behavioral Similarity in Bullying

To understand children's peer group affiliation, this study examined to what extent children in naturally occurring groups resemble each other on bullying, likeability, and perceived popularity. Participants were fourth‐ to sixth‐grade pupils (N = 461). Peer groups were identified using the social cognitive map procedure. Resemblance on bullying, likeability, and perceived popularity was evaluated by means of variance components models. Resemblance in peer groups was strongest for perceived popularity, followed by bullying and likeability. Moreover, resemblance on bullying could for a large part be attributed to the high‐perceived popularity of the group, and to a lesser extent, to the low likeability of the group. It is concluded that children showing bullying seem to affiliate with each other most of all to attain or maintain their position in a perceived popular peer group. Results stress the importance of considering the functionality of bullying from a group perspective.     

Predictors of Antisocial and Prosocial Behavior in an Adolescent Sports Context

This study examined antisocial and prosocial behavior of N = 439 adolescent athletes between 14 and 17 years of age (67 teams). Multi‐level analyses showed that team membership explained 20 and 13 percent of the variance in antisocial and prosocial behavior in the sports context, respectively. The team effects suggest that aggregating antisocial or prosocial adolescents within teams may partially explain differences in antisocial and prosocial behavior among athletes in the sports context. A trend was found toward a relation between higher levels of moral reasoning within teams, and less antisocial behavior in the sports context. Favorable moral atmosphere was positively associated with more prosocial behavior in the sports context. Finally, supportive coach–athlete relationships were associated with both less antisocial and more prosocial behavior in the sports context.     

Power of the Neyman Smooth Test for Evaluating Multivariate Forecast Densities

We compare and investigate Neyman's smooth test, its components, and the Kolmogorov-Smirnov (KS) goodness-of-fit test for testing the uniformity of multivariate forecast densities. Simulations indicate that the KS test lacks power when the forecast distributions are misspecified, especially for correlated sequences of random variables. Neyman's smooth test and its components work well in samples of size typically available, although there sometimes are size distortions. The components provide directed diagnosis regarding the kind of departure from the null. For illustration, the tests are applied to forecast densities obtained from a bivariate threshold model fitted to high-frequency financial data.     

Principles for Conduct of Pest Risk Analyses: Report of an Expert Workshop

The North American Free Trade Agreement (NAFTA) and the General Agreement on Tariffs and Trade (GATT) have focused attention on risk assessment of potential insect, weed, and animal pests and diseases of livestock. These risks have traditionally been addressed through quarantine protocols ranging from limits on the geographical areas from which a product may originate, postharvest disinfestation procedures like fumigation, and inspections at points of export and import, to outright bans. To ensure that plant and animal protection measures are not used as nontariff trade barriers, GATT and NAFTA require pest risk analysis (PRA) to support quarantine decisions. The increased emphasis on PRA has spurred multiple efforts at the national and international level to design frameworks for the conduct of these analyses. As approaches to pest risk analysis proliferate, and the importance of the analyses grows, concerns have arisen about the scientific and technical conduct of pest risk analysis. In January of 1997, the Harvard Center for Risk Analysis (HCRA) held an invitation-only workshop in Washington, D.C. to bring experts in risk analysis and pest characterization together to develop general principles for pest risk analysis. Workshop participants examined current frameworks for PRA, discussed strengths and weaknesses of the approaches, and formulated principles, based on years of experience with risk analysis in other setting and knowledge of the issues specific to analysis of pests. The principles developed highlight the both the similarities of pest risk analysis to other forms of risk analysis, and its unique attributes.     

Modelling step-families

A combined marco-micro model is applied to a population similar to that forecast for 2035 in the Netherlands in order to simulate the effect on kinship networks of a mating system of serial monogamy. The importance of incorporating a parameter for the degree of concentration of childbearing over the female population is emphasized. The inputs to the model are vectors of fertility rates by age of mother, and by age of father, a matrix of first-marriage rates by age of both partners (used in the macro-analytical expressions), and two parametersH andS (used in the micro-simulation phase). The output is a data base of hypothetical individuals, whose records contain identification number, age, sex, and the identification numbers of their relatives.     

A time-varying measurement error model for age of onset of a psychiatric diagnosis: applied to first depressive episode diagnosed by the Composite International Diagnostic Interview (CIDI)

A substantial degree of uncertainty exists surrounding the reconstruction of events based on memory recall. This form of measurement error affects the performance of structured interviews such as the Composite International Diagnostic Interview (CIDI), an important tool to assess mental health in the community. Measurement error probably explains the discrepancy in estimates between longitudinal studies with repeated assessments (the gold-standard), yielding approximately constant rates of depression, versus cross-sectional studies which often find increasing rates closer in time to the interview. Repeated assessments of current status (or recent history) are more reliable than reconstruction of a person's psychiatric history based on a single interview. In this paper, we demonstrate a method of estimating a time-varying measurement error distribution in the age of onset of an initial depressive episode, as diagnosed by the CIDI, based on an assumption regarding age-specific incidence rates. High-dimensional non-parametric estimation is achieved by the EM-algorithm with smoothing. The method is applied to data from a Norwegian mental health survey in 2000. The measurement error distribution changes dramatically from 1980 to 2000, with increasing variance and greater bias further away in time from the interview. Some influence of the measurement error on already published results is found.