Network Embeddedness in Exploration and Exploitation of Joint R&D Projects: A Structural Approach

This paper analyses how network embeddedness affects the exploration and exploitation of R&D project performance. By developing joint projects, partners and projects are linked to one another and form a network that generates social capital. We examine how the location, which determines the access to information and knowledge within a network of relationships, affects the performance of projects. We consider this question in the setup of exploration and exploitation projects, using a database built from an EU framework. We find that each of the structural embeddedness dimensions (degree, betweenness and eigenvector centrality) have a different impact on the exploration and exploitation project performance. Our empirical analysis extends to project management literature and social capital theory, by including the effect that the acquisition of external knowledge has on the performance of the project.     

Nonparametric Estimation of the Number of Drug Users in Hong Kong Using Repeated Multiple Lists

We update a previous approach to the estimation of the size of an open population when there are multiple lists at each time point. Our motivation is 35 years of longitudinal data on the detection of drug users by the Central Registry of Drug Abuse in Hong Kong. We develop a two‐stage smoothing spline approach. This gives a flexible and easily implemented alternative to the previous method which was based on kernel smoothing. The new method retains the property of reducing the variability of the individual estimates at each time point. We evaluate the new method by means of a simulation study that includes an examination of the effects of variable selection. The new method is then applied to data collected by the Central Registry of Drug Abuse. The parameter estimates obtained are compared with the well known Jolly–Seber estimates based on single capture methods.     

Comparison of hazard rates for dependent random variables

In this paper, we define and study a new notion for the comparison of the hazard rates of two random variables taking into account their mutual dependence. Properties, applications and the comparison for a data set are given.     

Validation of Nonparametric Two-sample Bootstrap in ROC Analysis on Large Datasets

The nonparametric two-sample bootstrap is applied to computing uncertainties of measures in receiver operating characteristic (ROC) analysis on large datasets in areas such as biometrics, speaker recognition, etc. when the analytical method cannot be used. Its validation was studied by computing the standard errors of the area under ROC curve using the well-established analytical Mann–Whitney statistic method and also using the bootstrap. The analytical result is unique. The bootstrap results are expressed as a probability distribution due to its stochastic nature. The comparisons were carried out using relative errors and hypothesis testing. These match very well. This validation provides a sound foundation for such computations.     

Investigating impacts of complex sampling on latent growth curve modelling

We investigate the impacts of complex sampling on point and standard error estimates in latent growth curve modelling of survey data. Methodological issues are illustrated with empirical evidence from the analysis of longitudinal data on life satisfaction trajectories using data from the British Household Panel Survey, a national representative survey in Great Britain. A multi-process second-order latent growth curve model with conditional linear growth is used to study variation in the two perceived life satisfaction latent factors considered. The benefits of accounting for the complex survey design are considered, including obtaining unbiased both point and standard error estimates, and therefore correctly specified confidence intervals and statistical tests. We conclude that, even for the rather elaborated longitudinal data models that were considered, estimation procedures are affected by variance-inflating impacts of complex sampling.     

Obesity and hospitalization over the adult life course: does duration of exposure increase use?

Consistent with a new genre of research on life-course analyses of health-service use, this study explores the consequences of long-term exposure to a risk factor. Drawing from cumulative-disadvantage theory, the study examines whether obesity, especially chronic obesity, increases hospitalization admission and length of stay. Analyses make use of hospital records abstracted over 20 years from a national survey of adults 41 to 77 years of age at baseline (n = 4,574). Multiple measures of body weight are used to calculate adult obesity duration. Results reveal that obesity increased hospital admissions and length of stay over the 20 years studied. Among persons obese at any time during the study, years of obesity also led to longer stays. The findings highlight the utility of measures of the duration of risk exposure for both life-course studies of health and tests of cumulative-disadvantage theory.     

First stirrings: cultural notes on orgasm, ejaculation, and wet dreams

Both the findings and the limitations of numeric milestone research in sexology have a bearing on the pedagogical status of pleasure, as well as the cultural underpinnings of the notion of a psychosexual milestone. An overview is offered of international data pertaining to the chronology of three "milestones" in sexual autobiography: first orgasm (orgasmarche), first ejaculation (oigarche), and first wet dream (nocturnal emission). Methodological problems associated with the measurement of these variables are discussed. These problems are then situated in a culturalist perspective. It is concluded that orgasms are cultural artifacts in terms of their chronological occurrence as well as perceived salience, necessity, and "age appropriateness".