A joint-modeling approach to assess the impact of biomarker variability on the risk of developing clinical outcome

In some clinical trials and epidemiologic studies, investigators are interested in knowing whether the variability of a biomarker is independently predictive of clinical outcomes. This question is often addressed via a naïve approach where a sample-based estimate (e.g., standard deviation) is calculated as a surrogate for the “true” variability and then used in regression models as a covariate assumed to be free of measurement error. However, it is well known that the measurement error in covariates causes underestimation of the true association. The issue of underestimation can be substantial when the precision is low because of limited number of measures per subject. The joint analysis of survival data and longitudinal data enables one to account for the measurement error in longitudinal data and has received substantial attention in recent years. In this paper we propose a joint model to assess the predictive effect of biomarker variability. The joint model consists of two linked sub-models, a linear mixed model with patient-specific variance for longitudinal data and a full parametric Weibull distribution for survival data, and the association between two models is induced by a latent Gaussian process. Parameters in the joint model are estimated under Bayesian framework and implemented using Markov chain Monte Carlo (MCMC) methods with WinBUGS software. The method is illustrated in the Ocular Hypertension Treatment Study to assess whether the variability of intraocular pressure is an independent risk of primary open-angle glaucoma. The performance of the method is also assessed by simulation studies.     

An International Comparative Study on Job Mobility

Abstract. Job mobility refers to the movement of people between jobs with different employers. It is an important means of adjustment in the labour market because it facilitates structural changes in the economy. This paper presents the results of a comparative study on job mobility in 6 countries: France, Japan, the Netherlands, Sweden, United Kingdom and the USA. Some of these countries use both labour force surveys and establishment surveys to gather information on job mobility, while other countries only use one of them. The paper uses information from both types of survey held in the seventies and the eighties and describes the developments and the structure of job mobility in the 6 countries. An empirical cross-country analysis shows that job mobility is positively correlated with the growth of employment and negatively correlated with the unemployment rate. There appear to be hardly any structural differences in job mobility between the USA, Sweden, France and the UK. Job mobility in the Netherlands is structurally lower than in the other countries, while job mobility in Japan is structurally lower than in the Netherlands.     

The Value of Supplier Information to Improve Management of a Retailer's Inventory

The distribution of lead time demand is essential for determining reorder points in inventory systems. Usually, the distribution of lead time demand is approximated directly. However, in some cases it may be worthwhile to take the demand per unit time and lead time into account, particularly when specific information is available. This paper deals with the situation where a supplier, who produces on order in fixed production cycles, provides information on the status of the coming production run. The retailer can use this information to gain insight into the lead-time process. A fixed order (s_vQ) strategy is presented, with a set of reorder points s_v depending on the time t until the first possible delivery, which is determined by the information of the supplier. A Markov model that analyzes a given (s_vQ) strategy is used to quantify the value of the information provided by the supplier. Some numerical examples show that the approach may lead to considerable cost savings compared to the traditional approach that uses only one single reorder point, based on a two-moments approximation. Using this numerical insight, the pros and cons of a more frequent exchange of information between retailers and suppliers can be balanced.     

The influence of the birthplace and models of care on midwifery practice for the management of women in labour

This paper will examine how the settings in which midwives practice (the birthplace) and models of care affect midwives’ decision making during the management of labour. One-hundred-and-four independent, team and hospital based midwives and 100 low obstetric risk nulliparous women to whom labour care was provided were surveyed. These midwives and women resided in the Auckland metropolitan area of New Zealand. The majority of midwives who participated worked in models of care which provided women with continuity of carer and care, however, this was not found to influence the way the midwives provided labour care. Instead, practice was found to be relatively homogenous regardless of whether the midwives worked in independent, team, or hospital-based practice. The birthplace setting in which the labour care took place did influence midwifery practice. The majority of midwives provided labour care in large obstetric hospitals and identified practices dominated by the medical model of care. Practice was described as being influenced by intervention and the need for technology, however, this did not prevent the majority of women from perceiving they were actively involved in the decision making process and that they worked in partnership with their midwives. Closer examination of the midwives’ decision making processes whilst providing the labour care revealed that the midwives’ individual decisions were influenced by the needs of the women rather than the hospital protocols. What became evident was that the midwives in this study had adopted a humanistic approach to care whereby technology was used alongside relationship-centred care.     

Job-related diversity: the comprehensiveness and speed of board decision-making processes—an upper echelons approach

Strategic decision-making processes influence firm-level outcomes. Using the theory of upper echelons, this study investigates how diversity in directors’ skills, knowledge, and industry experience influence board decision-making processes that may impact overall strategic decision-making processes. Such diversity has been commonly accepted to be a ‘double-edged sword’—enhancing comprehensiveness but hindering the speed of decision-making. On the contrary, we used an existing large survey database to show that directors’ diverse educational background, functional background, and industry experience (job-related diversity) have a positive effect on comprehensiveness as well as the speed of board decision-making. In addition, our results indicate that board processes (directors’ use of their knowledge and skills) play an important role by transmitting the positive effects of diversity. The study is in a tradition of exploring how boards may influence firms’ strategic decision-making processes. Our findings provide additional arguments for adding job-related diversity to boards of directors.     

The Efficacy of Local Governance Arrangements in Relation to Homelessness. A Comparison of Copenhagen,Glasgow, and Amsterdam

Over the last decade, several northern European metropolitan cities have developed new strategies to deal with homelessness. This article focuses on the efficacy of these new local governance arrangements in terms of service delivery and the related societal effects. By comparing and evaluating the policies, administrative structures and management styles in Copenhagen, Glasgow and Amsterdam, a better understanding is gained of the elements of local governance arrangements that influence the quality of service delivery for the homeless and benefit clients and society at large. The research findings lead to a critical view of current decentralizing trends.     

Incorporating Neighborhood Choice in a Model of Neighborhood Effects on Income

Studies of neighborhood effects often attempt to identify causal effects of neighborhood characteristics on individual outcomes, such as income, education, employment, and health. However, selection looms large in this line of research, and it has been argued that estimates of neighborhood effects are biased because people nonrandomly select into neighborhoods based on their preferences, income, and the availability of alternative housing. We propose a two-step framework to disentangle selection processes in the relationship between neighborhood deprivation and earnings. We model neighborhood selection using a conditional logit model, from which we derive correction terms. Driven by the recognition that most households prefer certain types of neighborhoods rather than specific areas, we employ a principle components analysis to reduce these terms into eight correction components. We use these to adjust parameter estimates from a model of subsequent neighborhood effects on individual income for the unequal probability that a household chooses to live in a particular type of neighborhood. We apply this technique to administrative data from the Netherlands. After we adjust for the differential sorting of households into certain types of neighborhoods, the effect of neighborhood income on individual income diminishes but remains significant. These results further emphasize that researchers need to be attuned to the role of selection bias when assessing the role of neighborhood effects on individual outcomes. Perhaps more importantly, the persistent effect of neighborhood deprivation on subsequent earnings suggests that neighborhood effects reflect more than the shared characteristics of neighborhood residents: place of residence partially determines economic well-being.