Evolution of recurrent asthma event rate over time in frailty models

Summary. To model the time evolution of the event rate in recurrent event data a crucial role is played by the timescale that is used. Depending on the timescale selected the interpretation of the time evolution will be entirely different, both in parametric and semiparametric frailty models. The gap timescale is more appropriate when studying the recurrent event rate as a function of time since the last event, whereas the calendar timescale keeps track of actual time. We show both timescales in action on data from an asthma prevention trial in young children. The frailty model is further extended to include both timescales simultaneously as this might be most relevant in practice.     

Comparing Public and Private Sector Decision-Making Practices

Public and private sector decision making is studied with anexperiment. The study compares decision making in a tax-supportedgeneral purpose governmental agency with that done by a businessfirm selling to a market, using a simulation to capture differencesin the preferences and practices of mid-level managers workingin the two sectors. The simulation calls for participating managersto assess the risk and prospect of adopting budgets tailoredto match each sector. A cognitive culture that stresses analysis,speculation, bargaining, or networking is employed to fashiona budget appropriate for a public and a private sector organization,each with a controversial and a noncontroversial budget amount.The literature on public/private differences was consulted tomake predictions, suggesting that public sector managers wouldfavor bargaining and networking and private sector managerswould favor analysis and speculation. The cognitive style literaturesuggests that managers favor budgets constructed with an approachthat is consistent with their preferred cognitive style andsee less risk in the choice, except in a public setting whererisk would be unaffected. The study finds that private sectormanagers are more apt to support budget decisions made withanalysis and less likely to support them when bargaining isapplied. Public sector managers are less likely to support budgetdecisions backed by analysis and more likely to support thosethat are derived from bargaining with agency people.     

Cultural Context in Career Theory and Practice: Role Salience and Values

Career theory and practice have long emphasized person variables (e.g., abilities, needs, interests) and have only recently begun focusing on environmental variables in addressing cultural context issues. Contemporary emphasis on contextual variables reflects notable movement toward attaining cultural relevance in career theory and practice. Role salience and values, which are central to developmental perspectives on career and have been considered in other approaches, are key contextual variables that can be examined to make additional progress toward this goal. The author argues that examining the cultural dimensions of social roles and values can enrich theory and enhance practice regarding life‐career development.     

On the Value of derivative evaluations and random walk suppression in Markov Chain Monte Carlo algorithms

Two strategies that can potentially improve Markov Chain Monte Carlo algorithms are to use derivative evaluations of the target density, and to suppress random walk behaviour in the chain. The use of one or both of these strategies has been investigated in a few specific applications, but neither is used routinely. We undertake a broader evaluation of these techniques, with a view to assessing their utility for routine use. In addition to comparing different algorithms, we also compare two different ways in which the algorithms can be applied to a multivariate target distribution. Specifically, the univariate version of an algorithm can be applied repeatedly to one-dimensional conditional distributions, or the multivariate version can be applied directly to the target distribution.     

Non-parametric Back-projection of HIV Positive Tests using Multinomial and Poisson Settings

Back-projection is a commonly used method in reconstructing HIV incidence. Instead of using AIDS incidence data in back-projection, this paper uses HIV positive tests data. Both multinomial and Poisson settings are used. The two settings give similar results when a parametric form or step function is assumed for the infection curve. However, this may not be true when the HIV infection in each year is characterized by a different parameter. This paper attempts to use simulation studies to compare these two settings by constructing various scenarios for the infection curve. Results show that both methods give approximately the same estimates of the number of HIV infections in the past, whilst the estimates for HIV infections in the recent past differ a lot. The multinomial setting always gives a levelling-off pattern for the recent past, while the Poisson setting is more sensitive to the change in the shape of the HIV infection curve. Nonetheless, the multinomial setting gives a relatively narrower point-wise probability interval. When the size of the epidemic is large, the narrow probability interval may be under-estimating the true underlying variation.     

Coping with War: Three Strategies Employed by Adolescent Citizens of Sierra Leone

Children and adolescents in Sierra Leone have suffered through a decade of catastrophic violence and dislocation resulting from a brutal civil war. Many have been forced to flee their villages and have found refuge in United Nations refugee camps in neighboring countries. These children have witnessed the torture, maiming, and murder of family, friends, and neighbors. Some have been forced to carry arms or to serve as domestic and sexual servants to predatory rebel combatants. All have confronted enormous hardship and loss. This paper identifies three coping strategies employed by adolescents in a large refugee camp. Implications for professional practice are discussed.     

Continuous-time capture-recapture models with time variation and behavioural response

This paper develops a likelihood-based inference procedure for continuous-time capture-recapture models. The first-capture and recapture intensities are assumed to be in constant proportion but may otherwise vary arbitrarily through time. The full likelihood is partitioned into two factors, one of which is analogous to the likelihood in a special type of multiplicative intensity model arising in failure time analysis. The remaining factor is free of the non-parametric nuisance parameter and is easily maximized. This factor provides an estimator of population size and an asymptotic variance under a counting process framework. The resulting estimation procedure is shown to be equivalent to that derived from a martingale-based estimating function approach. Simulation results are presented to examine the performance of the proposed estimators.