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.     

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.     

Modelling human immunodeficiency virus ribonucleic acid levels with finite mixtures for censored longitudinal data

The measurement of human immunodeficiency virus ribonucleic acid levels over time leads to censored longitudinal data. Suitable models for dynamic modelling of these levels need to take this data characteristic into account. If groups of patients with different developments of the levels over time are suspected the model class of finite mixtures of mixed effects models with censored data is required. We describe the model specification and derive the estimation with a suitable expectation-maximization algorithm. We propose a convenient implementation using closed form formulae for the expected mean and variance of the truncated multivariate distribution. Only efficient evaluation of the cumulative multivariate normal distribution function is required. Model selection as well as methods for inference are discussed. The application is demonstrated on the clinical trial ACTG 315 data.     

A team level investigation of the relationship between Leader–Member Exchange (LMX) differentiation,and commitment and performance

Although the differential treatment of team members by their leader is at the heart of Leader–Member Exchange (LMX) theory, empirical studies exploring the role of within-team LMX differentiation in relation to team outcomes are still relatively scarce. This study among 269 Dutch secondary school teachers from 33 different teams tested the hypotheses that the relationship between LMX differentiation and team commitment, and team performance is moderated by LMX-quality median. Moreover, we hypothesized that team members' perceived dissimilarity regarding work values and orientations would be positively related to within-team LMX differentiation. Teachers completed questionnaires on LMX-quality, dissimilarity, and team commitment, whereas team performance was rated by school principals. Results indeed showed that LMX differentiation is positively related to both outcome variables in teams with a low LMX-quality median only. As expected, more perceived dissimilarity between team members was related to more within-team variability in LMX-scores. These results contribute to knowledge on hypothetical antecedents and consequences of LMX differentiation at the team level.