Some characterizations of multivariate distributions using products of the hazard gradient and mean residual life components

We give a general procedure to characterize multivariate distributions by using products of the hazard gradient and mean residual life components. This procedure is applied to characterize multivariate distributions as Gumbel exponential, Lomax, Burr, Pareto and generalized Pareto multivariate distributions. Our results extend the results of several authors and can be used to study how to extend univariate models to the multivariate set-up.     

Approaches to conflict modeling: A study of a possible USA-USSR nuclear confrontation

A possible nuclear confrontation between the USA and USSR is analyzed using five different models from game theory in order to compare the various approaches that can be taken in the analysis of conflicts. Of particular importance is an improved metagame analysis model that provides a comprehensive procedure for analyzing not only the nuclear conflict but also any other type of real world conflict that can arise in practice. When the improved metagame analysis model is linked with a new state transition model, the dynamics of the game can be thoroughly studied.     

The raise estimator estimation,inference, and properties

Several methods using different approaches have been developed to remedy the consequences of collinearity. To the best of our knowledge, only the raise estimator proposed by García et al. (2010 García, C.B., García, J., Soto, J. (2010). The raise method: An alternative procedure to estimate the parameters in presence of collinearity. Qual. Quantity 45(2):403–423.[Crossref], [Web of Science ®] , [Google Scholar]) deals with this problem from a geometric perspective. This article fully develops the raise estimator for a model with two standardized explanatory variables. Inference in the raise estimator is examined, showing that it can be obtained from ordinary least squares methodology. In addition, contrary to what happens in ridge regression, the raise estimator maintains the coefficient of determination value constant. The expression of the variance inflation factor for the raise estimator is also presented. Finally, a comparative study of the raise and ridge estimators is carried out using an example.     

The influence of nutritional factors on prostate cancer incidence and aggressiveness

There is an increasing evidence for a link between nutrition, lifestyle and prostate cancer (PCa) development and/or progression of disease. The objective of this study was to examine the association between dietary factors and PCa incidence and aggressiveness in a case-control study. After the analysis of the anatomic pathology, subjects were classified in patients with PCa (n?=?157) and controls (n?=?158). Clinical data including Gleason score, PSA values and biopsy results, were compiled. Frequencies of food consumption and sociodemographic data were also obtained. The results showed that physical activity was significantly higher in control (p?p?=?.041) and fish (p?=?.041) intakes. Moreover, there was a significant reduction in risk (p?=?.029) in cases with a higher fruits and vegetables intakes. A decreased risk of aggressive PCa was associated with fruits, vegetables, legumes and fish intakes. However, these relationships were not statistically significant when data were adjusted for covariates. In conclusion, this study found an inverse association between PCa risk and the intake of fruits and vegetables, fish and nuts. The results suggested that a diet with higher intakes of these foods as Mediterranean diet may lower the risk of PCa in the studied population. As dietary factors are modifiable, identifying food groups or dietary patterns that modulate the risk of PCa and its aggressiveness can offer effective and practical strategies for its primary prevention.     

The National Work–Life Balance Index©: The European Case

More than 5 years since the outbreak of the global financial crisis, a flurry of evidence is emerging on the effects of the ensuing economic downturn on unemployment and poverty rates in rich countries, but less is known about cross-country differences in subjective assessments of the crisis and whether adults in households with children were affected to a greater extent. This paper investigates differences in the perceived impact of the economic crisis between adults in households with and without children in 17 European countries, using data from the Life in Transition Survey 2010 in a multilevel modelling framework. It also explores differences in the coping strategies that households adopted to deal with the decline in income or economic activity. Everything else being equal, perceptions of the crisis were more widespread in countries with higher rates of child poverty, lower economic growth and lower GDP per capita. Across countries, perceptions of the crisis closely trailed subjective indicators of financial difficulties from other international surveys conducted in 2010. Adults in households with children were more likely to report an impact of the crisis, with larger differences in countries with higher rates of monetary child poverty. Adults in households with children also adopted a greater variety of coping strategies than the rest, prioritizing expenditure on basic necessities, while cutting back on luxuries and holidays. Nevertheless, many still reported reduced consumption of staple foods as a result of economic difficulties.     

On a log-symmetric quantile tobit model applied to female labor supply data

The study of female labor supply has been a topic of relevance in the economic literature. Generally, the data are left-censored and the classic tobit model has been extensively used in the modeling strategy. This model, however, assumes normality for the error distribution and is not recommended for data with positive skewness, heavy-tails and heteroscedasticity, as is the case of female labor supply data. Moreover, it is well-known that the quantile regression approach accounts for the influences of different quantiles in the estimated coefficients. We take all these features into account and propose a parametric quantile tobit regression model based on quantile log-symmetric distributions. The proposed method allows one to model data with positive skewness (which is not suitable for the classic tobit model), to study the influence of the quantiles of interest, and to account for heteroscedasticity. The model parameters are estimated by maximum likelihood and a Monte Carlo experiment is performed to evaluate alternative estimators. The new method is applied to two distinct female labor supply data sets. The results indicate that the log-symmetric quantile tobit model fits better the data than the classic tobit model.     

Social norms, partnerships and children

This paper presents a social norms interpretation to explain cross-country differences in partnership formation rates. Social norms are modeled as a constraint on the allocation of household labor that diminishes the gains of entering a partnership, especially for highly educated women with a higher opportunity cost of time. Results using individual level data from 7 waves of the European Community Household Panel (1995?C2001) confirm the predictions from the theory. These results are robust to controlling for country varying factors such as childcare policies and divorce rates, and are mostly driven by marriage (as opposed to cohabitation) decisions. Given that household formation is a necessary prerequisite to having children, our results potentially shed light onto the process of below replacement fertility and the economic challenges associated with it.     

HIV seroprevalence and risk behaviors among clients attending a clinic for the homeless in Miami/Dade County,Florida, 1990–1996

In the early 1990s, HIV seroprevalence was highest at the Miami homeless clinic among 16 homeless sites participating in a nationwide sentinel survey. To examine dynamic seroprevalence patterns in Miami's homeless clients in relation to demographics and risk behaviors over six years, we analyzed data from an unlinked (blinded) serosurvey of clients attending the principal primary care clinic serving Miami's homeless. Data were from 3,797 medical encounters with homeless persons who, on their initial clinic visit within an annual survey period, received routine serologic testing and a risk behavior survey. Overall HIV seroprevalence was 15.9% and infection rates for men (16.4%) and women (14.5%) did not differ. Seroprevalence for blacks (19.9%) was significantly higher than for Hispanics (9.1%) or whites (8.3%) (p < 0.0001). Seroprevalence was 12.6% (35 times the national rate) for clients reporting heterosexual contact as their only risk. Significant increases in seroprevalence, above this heterosexual-contact-only 'baseline', were found for clients disclosing high-risk behaviors: male-to-male sex, drug injection, receiving or giving money/drugs for sex, and sexual contact with a drug injector or HIV-infected partner (p < 0.0001). Seroprevalence declined over six years from 23.2 to 7.2% (p < 0.0001). Significant downward trends were observed for men and women, blacks and Hispanics, men who have sex with men, and clients reporting heterosexual contact. The proportion of clients reporting high-risk behaviors decreased sharply (p < 0.0001). Elevated HIV seroprevalence in Miami's homeless clients was strongly associated with high-risk behaviors. Expansion of HIV prevention and HIV/drug treatment services for homeless persons is strongly recommended.