The Role of the Demographic Transition in the Process of Urbanization

The next observation is, that … there are far more burials than christenings. This is plain…. From this single observation it will follow that London should have decreased in its people, the contrary whereof we see by its daily increase…. It is therefore certain that London is supplied with people from out of the country, whereby not only to repair the over‐plus difference of burials above‐mentioned, but likewise to increase its inhabitants—John Graunt, Natural and Political Observations made upon the Bills of Mortality.     

A Relational Gompertz Model of Male Fertility: Development and Assessment

Brass has proposed a relational Gompertz model of female fertility which, in combination with the standard fertility distribution developed by Booth, has proved useful in a range of applications, such as indirect estimation, demographic modelling, and population projections. This paper develops a standard distribution of male fertility for use in conjunction with the relational Gompertz model. The derivation of the standard takes advantage of the similarity between the shape of male and female fertility distributions. It entails ‘stretching’ the female standard, so that it extends to age 80, and then transforming it, using the Gompertz model into a pattern which is more typical of male fertility distributions in the developing world. An assessment of this new standard by fitting the relational Gompertz model based on it to a series of male fertility distributions from diverse populations, suggests that it performs very well.     

Generalized stochastic dominance and bad outcome aversion

Incomplete preferences over lotteries on a finite set of alternatives satisfying, besides independence and continuity, a property called bad outcome aversion are considered. These preferences are characterized in terms of their specific multi-expected utility representations (cf. Dubra et al., J Econ Theory, 115:118–133, 2004), and can be seen as generalized stochastic dominance preferences.     

Youth Justice

This paper illustrates how mindfulness and reflection exercises can be integrated into the teaching and learning of active listening skills, an integral component of relationship skills training. This pedagogy was first trialled on a small cohort of 15 students and the improved version was applied with a second cohort of 53 students. Through the mindfulness and reflection exercises which were built in throughout the module, students identified the three most prominent ‘bad habits’ that hindered active listening as ‘mind wandering’, ‘multi-tasking’ while listening and ‘thinking ahead’. The mindfulness and reflection exercises appeared to bring the usually-unnoticed ‘bad habits’ into awareness so that a conscious effort could be channelled into preventing them from interfering with relationship building. This expanded awareness facilitated the strengthening of ability to observe oneself in interactions. This paper proposes a combination of exercises that expand students' awareness of their own habitual listening styles, together with skills training through conventional methods of role play, video-taping and skills drilling, in order to strengthen motivation to change and bring about deeper learning.     

Blinded sample size re‐estimation in crossover bioequivalence trials

In drug development, bioequivalence studies are used to indirectly demonstrate clinical equivalence of a test formulation and a reference formulation of a specific drug by establishing their equivalence in bioavailability. These studies are typically run as crossover studies. In the planning phase of such trials, investigators and sponsors are often faced with a high variability in the coefficients of variation of the typical pharmacokinetic endpoints such as the area under the concentration curve or the maximum plasma concentration. Adaptive designs have recently been considered to deal with this uncertainty by adjusting the sample size based on the accumulating data. Because regulators generally favor sample size re‐estimation procedures that maintain the blinding of the treatment allocations throughout the trial, we propose in this paper a blinded sample size re‐estimation strategy and investigate its error rates. We show that the procedure, although blinded, can lead to some inflation of the type I error rate. In the context of an example, we demonstrate how this inflation of the significance level can be adjusted for to achieve control of the type I error rate at a pre‐specified level. Furthermore, some refinements of the re‐estimation procedure are proposed to improve the power properties, in particular in scenarios with small sample sizes. Copyright © 2014 John Wiley & Sons, Ltd.     

A comparison of subgroup identification methods in clinical drug development: Simulation study and regulatory considerations

With advancement of technologies such as genomic sequencing, predictive biomarkers have become a useful tool for the development of personalized medicine. Predictive biomarkers can be used to select subsets of patients, which are most likely to benefit from a treatment. A number of approaches for subgroup identification were proposed over the last years. Although overviews of subgroup identification methods are available, systematic comparisons of their performance in simulation studies are rare. Interaction trees (IT), model‐based recursive partitioning, subgroup identification based on differential effect, simultaneous threshold interaction modeling algorithm (STIMA), and adaptive refinement by directed peeling were proposed for subgroup identification. We compared these methods in a simulation study using a structured approach. In order to identify a target population for subsequent trials, a selection of the identified subgroups is needed. Therefore, we propose a subgroup criterion leading to a target subgroup consisting of the identified subgroups with an estimated treatment difference no less than a pre‐specified threshold. In our simulation study, we evaluated these methods by considering measures for binary classification, like sensitivity and specificity. In settings with large effects or huge sample sizes, most methods perform well. For more realistic settings in drug development involving data from a single trial only, however, none of the methods seems suitable for selecting a target population. Using the subgroup criterion as alternative to the proposed pruning procedures, STIMA and IT can improve their performance in some settings. The methods and the subgroup criterion are illustrated by an application in amyotrophic lateral sclerosis.     

Using Cost Per Use to Assess Big Deals

This presentation from the 23rd North Carolina Serials Conference discussed the Carolina Consortium's recent consortium-wide analysis of its big deal ejournal packages, with cost per use as the primary metric. This session addressed the pros and cons of cost-per-use (CPU) data and considered how consortia and individual schools should best utilize the data. Bernhardt discussed how the Carolina Consortium gathered and analyzed CPU data and the impact the examination had on determining whether individual schools cancelled, renewed, or joined big deals. Seven schools were identified as having big deals with CPU higher than desired. Of those seven, four schools chose to renew their deals, while three chose to cancel. Bucknall determined that while CPU is an important metric to analyze in making renewal and cancellation decisions, it is not the only factor.     

Bayesian analysis of mark‐recapture data with travel time‐dependent survival probabilities

The authors extend the classical Cormack‐Jolly‐Seber mark‐recapture model to account for both temporal and spatial movement through a series of markers (e.g., dams). Survival rates are modeled as a function of (possibly) unobserved travel times. Because of the complex nature of the likelihood, they use a Bayesian approach based on the complete data likelihood, and integrate the posterior through Markov chain Monte Carlo methods. They test the model through simulations and apply it also to actual salmon data arising from the Columbia river system. The methodology was developed for use by the Pacific Ocean Shelf Tracking (POST) project.     

Tax Structure and Female Labour Supply: Evidence from Ireland

How great an effect does the structure of income taxes have on female labour supply? This issue is investigated using a discrete‐choice static labour supply model for married couples in Ireland. The model incorporates fixed costs of working and simultaneously explains participation decisions and preferred hours of work. The model is estimated using data from the 1994 wave of the Living in Ireland Survey. Simulations examine the labour supply effects of introducing greater independence in the tax treatment of married couples, compared with an income‐splitting system, and alternative forms of tax cuts.