On Combining Wavelets Expansion and Sparse Linear Models for Regression on Metabolomic Data and Biomarker Selection

Wavelet thresholding of spectra has to be handled with care when the spectra are the predictors of a regression problem. Indeed, a blind thresholding of the signal followed by a regression method often leads to deteriorated predictions. The scope of this article is to show that sparse regression methods, applied in the wavelet domain, perform an automatic thresholding: the most relevant wavelet coefficients are selected to optimize the prediction of a given target of interest. This approach can be seen as a joint thresholding designed for a predictive purpose. The method is illustrated on a real world problem where metabolomic data are linked to poison ingestion. This example proves the usefulness of wavelet expansion and the good behavior of sparse and regularized methods. A comparison study is performed between the two-steps approach (wavelet thresholding and regression) and the one-step approach (selection of wavelet coefficients with a sparse regression). The comparison includes two types of wavelet bases, various thresholding methods, and various regression methods and is evaluated by calculating prediction performances. Information about the location of the most important features on the spectra was also obtained and used to identify the most relevant metabolites involved in the mice poisoning.     

A Note on Selection and Gender Unemployment Gaps

Previous research has documented the impact of positive selection into employment on the ranking of countries by gender wage gaps. This note focuses on the impact of selection into labor force on cross-country differences in gender unemployment gaps. We construct the Manski bounds for the selection-free gender unemployment gaps in 26 EU countries and show that - without additional assumptions - the observed gender unemployment gaps carry little information about the selection-free gender differences in unemployment. Contrary to the common assumption of positive selection into labor force (similar to positive selection into employment documented in the gender wage gap research), we also point at an example of negative-selection bias. We show that labor force withdrawal of mothers on job-protected family leaves may lead to an overestimation of the selection-free gender unemployment gaps by as much as 1 p.p.     

Women’s Tertiary Education Masks the Gender Wage Gap in Turkey

This paper investigates the gender wage gap for full-time formal sector employees, disaggregated by education level. The gap between the labor force participation rate of women with tertiary education and those with lower levels of education is substantial. There is no such gap for men. Hence, existing gender wage gap studies for Turkey, where we observe lopsided labor force participation rates by education levels, compare two very different populations. We disaggregate the whole sample by education level to create more homogenous sub-groups. For Turkey, without disaggregation, the gender wage gap was 13% in 2011, and women are significantly over-qualified relative to men on observed characteristics. Once we disaggregate the sample by education level, we show that the gender wage gap is 24% for less educated women and 9% for women with tertiary education in full-time formal employment. Observed characteristics only explain 1 % of this gap in absolute terms. We further disaggregate the data by public and private employment. The gender gap is higher in the private sector. However, women with tertiary education in the public sector are significantly better qualified compared to men, and consequently the adjusted gender wage gap is higher for women with tertiary education in the public sector. Our estimates also indicate a rise in the gender wage gap between 2004 and 2011.     

Developing Age-Friendly Cities: Case Studies From Brussels and Manchester and Implications for Policy and Practice

Developing environments responsive to the aspirations of older people has become a major concern for social and public policy. Policies and programs directed at achieving “age-friendly” communities are considered to require a wide range of interventions, including actions at the level of the social and physical environment. This article compares the age-friendly approaches of two European cities, Brussels and Manchester, with a particular focus on policies and initiatives that promote active aging in an urban context. The article examines, first, the demographic, social, and multicultural contexts of Brussels and Manchester; second, the way in which both cities became members of the World Health Organization Global Network of Age-Friendly Cities and Communities; third, similarities and differences in the age-friendly approaches and actions adopted by both cities; and fourth, opportunities and barriers to the implementation of age-friendly policies. The article concludes by discussing the key elements and resources needed to develop age-friendly cities.     

Multilevel maximum likelihood estimation with application to covariance matrices

The asymptotic variance of the maximum likelihood estimate is proved to decrease when the maximization is restricted to a subspace that contains the true parameter value. Maximum likelihood estimation allows a systematic fitting of covariance models to the sample, which is important in data assimilation. The hierarchical maximum likelihood approach is applied to the spectral diagonal covariance model with different parameterizations of eigenvalue decay, and to the sparse inverse covariance model with specified parameter values on different sets of nonzero entries. It is shown computationally that using smaller sets of parameters can decrease the sampling noise in high dimension substantially.     

Semi-polynomial copulas

In this paper, we characterise a family of bivariate copulas whose sections between the main diagonal and the border of the unit square are polynomial, generalising several families of copulas, including those with quadratic and cubic sections. We also study a measure of association and the tail dependence for this class, illustrating our results with several examples.     

Resilience in low-income African American women living and aging with HIV

Women are living with HIV into middle and older age and are likely to face multiple comorbidities and stressors as they age. This study focused on understanding how women who experience multiple forms of oppression and ongoing adversity are still able to adapt and stand strong. Using a theoretical framework of resilience and a feminist research ideology, interviews of eight middle-aged and older African American women living with HIV were analyzed. Despite experiences of HIV-related discrimination, trauma, and violence, these women demonstrated a remarkable ability to adapt and maintain support. Implications for research and practice are discussed.     

Long-term care in Spain: Difficulties in professionalizing services

The aim of this article is to analyze the difficulties in professionalizing the long-term care system in Spain. Since 2006, the new Spanish law has recognized care as a subjective right, and regulations are being designed to create a framework for its professionalization. Nowadays, family remains the most important group of providers who care for their elders, and women remain the main informal caregivers. Why do families resist using public long-term care services and professional carers included in the new law? The hypothesis highlights sociocultural factors as an obstacle to professionalization of long-term care services in addition to political and economic factors. The results show qualitative data about expectations, preferences, and discourses that women caregivers have in relation to their responsibility. The empirical material includes 25 interviews with different profiles of caregivers and six focus groups with family caregivers. The article suggests that the Spanish ideal of care is a problem for the professionalization of services because the family remains as the main provider of care—without specific skills, knowledge, and abilities.