The analysis of age-specific fertility patterns via logistic models

In this paper, we introduce logistic models to analyse fertility curves. The models are formulated as linear models of the log odds of fertility and are defined in terms of parameters that are interpreted as measures of level, location and shape of the fertility schedule. This parameterization is useful for the evaluation, and interpretation of fertility trends and projections of future period fertility. For a series of years, the proposed models admit a state-space formulation that allows a coherent joint estimation of parameters and forecasting. The main features of the models compared with other alternatives are the functional simplicity, the flexibility, and the interpretability of the parameters. These and other features are analysed in this paper using examples and theoretical results. Data from different countries are analysed, and to validate the logistic approach, we compare the goodness of fit of the new model against well-known alternatives; the analysis gives superior results in most developed countries.     

University Students’ Attitudes Toward Same-Sex Parenting and Gay and Lesbian Rights in Portugal

The purpose of this study was to explore university students’ attitudes toward same-sex parenting and toward gay and lesbian rights. A total of 292 participants, aged between 18 and 27 (M = 21) responded to a questionnaire measuring attitudes toward parenting by gay men and lesbians, gay and lesbian rights, and beliefs about the etiology of homosexuality. Results revealed that the majority of students were against gay and lesbian parenting, gay and lesbian equal rights, and believed that homosexuality has a social/environmental basis. It was found that sexual prejudice is highly prevalent in Portuguese university students, and implications of these findings are discussed.     

Measuring non-linear dependence for two random variables distributed along a curve

We propose new dependence measures for two real random variables not necessarily linearly related. Covariance and linear correlation are expressed in terms of principal components and are generalized for variables distributed along a curve. Properties of these measures are discussed. The new measures are estimated using principal curves and are computed for simulated and real data sets. Finally, we present several statistical applications for the new dependence measures.     

Evidence-based practice: from medicine to social work

The last 10 years have witnessed an increasing interest in evidence-based practice in the field of medicine. The product of a time characterised by the explosion of information technology, a heightened sense of risk, and the enshrining of the principles of economy, effectiveness, transparency and consumerism, evidence-based practice has rapidly expanded from medicine to other fields, including social work. The new paradigm has generated not only great enthusiasm in many areas of the social work profession but also an intense debate about the transferability of the principles of evidence-based practice from medicine to a discipline that operates amidst particularly complex and multifaceted societal factors. Similarly, the concept of evidence upon which social work practice should be based has been the object of considerable discussion, though initial emphasis on results from randomised controlled trials seems to be gradually shifting towards broader approaches to defining evidence. Although organisational constraints and job pressures are likely to favour the use, among practitioners, of ‘preappraised’ resources, this should not prevent social workers from acquiring the skills and knowledge necessary to make independent and critical appraisal of evidence.     

Expert Judgment-Based Risk Assessment Using Statistical Scenario Analysis: A Case Study—Running the Bulls in Pamplona (Spain)

In this article, we present a methodology to assess the risk incurred by a participant in an activity involving danger of injury. The lack of high-quality historical data for the case considered prevented us from constructing a sufficiently detailed statistical model. It was therefore decided to generate a risk assessment model based on expert judgment. The methodology is illustrated in a real case context: the assessment of risk to participants in a San Fermin bull-run in Pamplona (Spain). The members of the panel of "experts on the bull-run" represented very different perspectives on the phenomenon: runners, surgeons and other health care personnel, journalists, civil defense workers, security staff, organizers, herdsmen, authors of books on the bull-run, etc. We consulted 55 experts. Our methodology includes the design of a survey instrument to elicit the experts' views and the statistical and mathematical procedures used to aggregate their subjective opinions.     

Nenparametric Two-Group Classification: Concepts and a SAS-Based Software Package

This article introduces BestClass, a set of SAS macros, available in the mainframe and workstation environment, designed for solving two-group classification problems using a class of recently developed nonparametric classification methods. The criteria used to estimate the classification function are based on either minimizing a function of the absolute deviations from the surface which separates the groups, or directly minimizing a function of the number of misclassified entities in the training sample. The solution techniques used by BestClass to estimate the classification rule use the mathematical programming routines of the SAS/OR software. Recently, a number of research studies have reported that under certain data conditions this class of classification methods can provide more accurate classification results than existing methods, such as Fisher's linear discriminant function and logistic regression. However, these robust classification methods have not yet been implemented in the major statistical packages, and hence are beyond the reach of those statistical analysts who are unfamiliar with mathematical programming techniques. We use a limited simulation experiment and an example to compare and contrast properties of the methods included in Best-Class with existing parametric and nonparametric methods. We believe that BestClass contributes significantly to the field of nonparametric classification analysis, in that it provides the statistical community with convenient access to this recently developed class of methods. BestClass is available from the authors.     

Human Error in Autonomous Underwater Vehicle Deployment: A System Dynamics Approach

The use of autonomous underwater vehicles (AUVs) for various applications have grown with maturing technology and improved accessibility. The deployment of AUVs for under-ice marine science research in the Antarctic is one such example. However, a higher risk of AUV loss is present during such endeavors due to the extremities in the Antarctic. A thorough analysis of risks is therefore crucial for formulating effective risk control policies and achieving a lower risk of loss. Existing risk analysis approaches focused predominantly on the technical aspects, as well as identifying static cause and effect relationships in the chain of events leading to AUV loss. Comparatively, the complex interrelationships between risk variables and other aspects of risk such as human errors have received much lesser attention. In this article, a systems-based risk analysis framework facilitated by system dynamics methodology is proposed to overcome existing shortfalls. To demonstrate usefulness of the framework, it is applied on an actual AUV program to examine the occurrence of human error during Antarctic deployment. Simulation of the resultant risk model showed an overall decline in human error incident rate with the increase in experience of the AUV team. Scenario analysis based on the example provided policy recommendations in areas of training, practice runs, recruitment policy, and setting of risk tolerance level. The proposed risk analysis framework is pragmatically useful for risk analysis of future AUV programs to ensure the sustainability of operations, facilitating both better control and monitoring of risk.     

Moral pride only under the positive gaze of others? Effects of praise and criticism on moral pride and guilt / ¿Orgullo moral solo bajo la mirada positiva de los otros? Los efectos del elogio y la crítica sobre el orgullo moral y la culpa

Abstract

This study analysed the influence of praise and criticism on moral pride (the pride we feel when we believe we have done something morally good) and guilt. Ninety-two adolescents (age: M = 15.17, SD = 0.43; 44.6% girls, 55.4% boys) completed a questionnaire which outlined 10 scenarios based on combinations of three variables: the moral nature of the action (positive/negative); praise, criticism or the absence of either; and the source (parents/peers). Participants were asked to indicate the intensity with which they would feel pride and guilt (seven-point scale). Praise of positive actions increased pride. Interestingly, criticism of positive actions reduced pride and increased guilt, while praise of negative actions reduced guilt and increased pride. No differences were found between the pride felt after a criticized positive action and that felt after a praised negative action. A parallel effect was not, however, observed for guilt. These results reveal the strong, sometimes pernicious, influence of praise and criticism on guilt and pride and, even more, the need for praise by others in the experience of moral pride.