Analysis of a marker for cancer of the thyroid with a limit of detection

Limit of detection (LoD) is a common problem in the analysis of data generated by instruments that cannot detect very small concentrations or other quantities, resulting in left-censored measurements. Methods intended for data that are not subject to this problem are often difficult to modify for censoring. We adapt the simulation-extrapolation method, devised originally for fitting models with measurement error, to dealing with LoD in conjunction with a mixture analysis. The application relates the levels of thyroglobulin in individuals with cancer of the thyroid before and after treatment with radioactive iodine I–131. We conclude that the fitted mixture components correspond to levels of effectiveness of the treatment.     

Non-homogeneous Markov models in the analysis of survival after breast cancer

A cohort of 300 women with breast cancer who were submitted for surgery is analysed by using a non-homogeneous Markov process. Three states are onsidered: no relapse, relapse and death. As relapse times change over time, we have extended previous approaches for a time homogeneous model to a non omogeneous multistate process. The trends of the hazard rate functions of transitions between states increase and then decrease, showing that a changepoint can be considered. Piecewise Weibull distributions are introduced as transition intensity functions. Covariates corresponding to treatments are incorporated in the model multiplicatively via these functions. The likelihood function is built for a general model with k changepoints and applied to the data set, the parameters are estimated and life-table and transition probabilities for treatments in different periods of time are given. The survival probability functions for different treatments are plotted and compared with the corresponding function for the homogeneous model. The survival functions for the various cohorts submitted for treatment are fitted to the mpirical survival functions.     

Classification of Poverty Condition Using Natural Language Processing

Social Indicators Research - This work introduces a methodology to classify between poor and extremely poor people through Natural Language Processing. The approach serves as a baseline to...     

Social innovation as a collaborative concept

The rise of social innovation expresses a discontent with innovation as we know it, and its ability to deliver just and sustainable outcomes. Yet, social innovation is also notoriously vague as a concept, thereby putting into doubt whether the concept offers any real improvements or alternatives. This paper issues an invitation to think about social innovation as a collaborative concept. The conceptual framework shows collaboration, rather than contestation, to offer a space for the working together of different perspectives and actors. The collaborative concept frame welcomes and seeks to explain a diversity of uses. Singling out key features of social innovation as a collaborative concept, it seeks to contribute to an emerging practice that makes different contributions part of a progressive conversation about social innovation, the evaluative ideas associated with it and the evidence from policies and projects. Identifying transformative, taxonomical and transitional–sceptical uses of social innovation, the paper highlights the importance of analysing the evaluative aspects of the multisectoral reconfigurations associated with social innovation so as to keep track of its role for justice and sustainability.     

From Rags to Riches? Immigration and Poverty in Spain

This article for first time explores the relationship between immigration and poverty in Spain. Using recent Spanish household surveys, it is found, first, that both moderate and severe poverty are more acute among immigrants than among nationals and social transfers play no substantial role in reducing monetary deprivation in the case of foreign-born population; in the second place, we perform an econometric analysis that shows that the different poverty risk faced by local and immigrant households is not driven by differences in basic household and demographic characteristics.     

Who speaks up to whom? A relational approach to employee voice

We adopt a relational approach to examine the effects of social relations and formal structure on who speaks up to whom about problems at work. Data were collected in a two-wave employee survey in three Dutch preschools. Using exponential random graph modeling, we found significant positive effects of formal structure (recipient's hierarchical level; team co-membership) and good relations between speaker and recipient on the likelihood of voice in a dyad. Speaker's hierarchical level had positive effects, significant in Wave 1. Speaker's degree centrality significantly reduced the likelihood of voice, whereas recipient's degree centrality had no effect.