Flexible parametric modelling of the hazard function in breast cancer studies

In cancer research, study of the hazard function provides useful insights into disease dynamics, as it describes the way in which the (conditional) probability of death changes with time. The widely utilized Cox proportional hazard model uses a stepwise nonparametric estimator for the baseline hazard function, and therefore has a limited utility. The use of parametric models and/or other approaches that enables direct estimation of the hazard function is often invoked. A recent work by Cox et al. [6 Cox, C., Chu, H., Schneider, M. F. and Munoz, A. 2007. Parametric survival analysis and taxonomy of hazard functions for the generalized gamma distribution. Stat. Med., 26: 4352–4374. [Crossref], [PubMed], [Web of Science ®] , [Google Scholar]] has stimulated the use of the flexible parametric model based on the Generalized Gamma (GG) distribution, supported by the development of optimization software. The GG distribution allows estimation of different hazard shapes in a single framework. We use the GG model to investigate the shape of the hazard function in early breast cancer patients. The flexible approach based on a piecewise exponential model and the nonparametric additive hazards model are also considered.     

Social security reform and the support for public education

Old age pensions and public education account for a large share of public budgets. We link both programs through a tax-transfer system that is also sensitive to labor market distortions. We analyze the impact that alternative pension reforms have, through the political process, on publicly financed education. We explain how changes in the pension system design affect the link between the two programs and also labor market incentives. These effects, if they exist, act in opposite directions. Overall, we find that most proposals that entail a partial privatization of pensions reduce the willingness of the society to fund public education.     

The complex Watson distribution and shape analysis

The complex Watson distribution is an important simple distribution on the complex sphere which is used in statistical shape analysis. We describe the density, obtain the integrating constant and provide large sample approximations. Maximum likelihood estimation and hypothesis testing procedures for one and two samples are described. The particular connection with shape analysis is discussed and we consider an application examining shape differences between normal and schizophrenic brains. We make some observations about Bayesian shape inference and finally we describe a more general rotationally symmetric family of distributions.     

Development of a Performance Assessment Capability in the Waste Management Programs of the U.S. Nuclear Regulatory Commission

The U.S. Nuclear Regulatory Commission (NRC) staff has developed a performance assessment capability to address three programmatic areas in nuclear waste management: high-level waste, low-level waste, and decommissioning of licensed facilities (license termination). The NRC capability consists of: (1) methodologies for performance assessment; (2) models and computer codes for estimating system performance; (3) regulatory guidance in various forms, such as regulations, Branch Technical Positions, and Standard Review Plans; and (4) a technical staff experienced in executing and evaluating performance assessments for a variety of waste systems. Although the tools and techniques are refined for each programmatic area, general approaches and similar issues are encountered in all areas.     

The Expected Value of Information and the Probability of Surprise

Risk assessors attempting to use probabilistic approaches to describe uncertainty often find themselves in a data-sparse situation: available data are only partially relevant to the parameter of interest, so one needs to adjust empirical distributions, use explicit judgmental distributions, or collect new data. In determining whether or not to collect additional data, whether by measurement or by elicitation of experts, it is useful to consider the expected value of the additional information. The expected value of information depends on the prior distribution used to represent current information; if the prior distribution is too narrow, in many risk-analytic cases the calculated expected value of information will be biased downward. The well-documented tendency toward overconfidence, including the neglect of potential surprise, suggests this bias may be substantial. We examine the expected value of information, including the role of surprise, test for bias in estimating the expected value of information, and suggest procedures to guard against overconfidence and underestimation of the expected value of information when developing prior distributions and when combining distributions obtained from multiple experts. The methods are illustrated with applications to potential carcinogens in food, commercial energy demand, and global climate change.     

ON FINDING AN INITIAL SOLUTION FOR THE DUAL SIMPLEX ALGORITHM

Torrance [4] has proposed a “new” approach to finding an initial solution of a linear programming problem for use in conjunction with the dual simplex algorithm. The purpose of this note is to comment on two aspects of that paper. Firstly, Torrance's method is not new at all, but was proposed in 1958 by Wagner. Secondly, the method can be implemented much more efficiently than Torrance suggests.     

Testing the Parent–Adolescent Acculturation Discrepancy Hypothesis: A Five‐Wave Longitudinal Study

This 2½‐year, 5‐wave longitudinal study tests the hypothesis that acculturation discrepancies between Hispanic immigrant parents and adolescents would lead to compromised family functioning, which would then lead to problematic adolescent outcomes. Recent‐immigrant Hispanic parent–adolescent dyads (N = 302) completed measures of acculturation and family functioning. Adolescents completed measures of positive youth development, depressive symptoms, problem behavior, and substance use. Results indicated that Time 1 discrepancies in Hispanic culture retention, and linear trajectories in some of these discrepancies, negatively predicted adolescent positive youth development, and positively predicted adolescent depressive symptoms and binge drinking, indirectly through adolescent‐reported family functioning. The vast majority of effects were mediated rather than direct, supporting the acculturation discrepancy hypothesis. Implications for further research and intervention are discussed.     

The Gambling Motives Questionnaire financial: factor structure,measurement invariance,and relationships with gambling behaviour

Items assessing financial motives were recently integrated with the Gambling Motives Questionnaire (GMQ), resulting in a revised measure that assesses coping, enhancement, social and financial motives for gambling (GMQ-F). The aim of this research was to test the proposed four-factor structure of the GMQ-F, determine if GMQ-F responses were invariant across sex, and test a structural model that specifies links between motives, gambling frequency and problem gambling severity. Telephone surveys were conducted with 932 adult gamblers from across Manitoba, Canada, who responded to items from the GMQ-F and reported their frequency of gambling and levels of problem gambling severity. Confirmatory factor analysis yielded strong support for the four-factor structure of GMQ-F scores, and invariance testing provided evidence of measurement invariance across sex. Finally, support was found for the hypothesized structural model in which each gambling motive predicted gambling frequency, which in turn predicted problem gambling severity. Coping motives also directly predicted problem gambling severity. These results provide strong evidence in support of the validity of GMQ-F responses, offer further support for the integration of financial motives with the GMQ, and delineate relationships between gambling motives, gambling frequency and gambling-related harm.