Graphical and Numerical Methods for Detecting Influential Observations in Complex Bingham Data

We describe methods to detect influential observations in a sample of pre-shapes when the underlying distribution is assumed to be complex Bingham. One of these methods is based on Cook's distance, which is derived from the likelihood of the complex Bingham distribution. Other method is related to the tangent space, which is based on the local influence for the multivariate normal distribution. A method to detect outliers is also explained. The application of the methods is illustrated in both a real dataset and a simulated sample.     

Diagnostics in elliptical regression models with stochastic restrictions applied to econometrics

We propose an influence diagnostic methodology for linear regression models with stochastic restrictions and errors following elliptically contoured distributions. We study how a perturbation may impact on the mixed estimation procedure of parameters in the model. Normal curvatures and slopes for assessing influence under usual schemes are derived, including perturbations of case-weight, response variable, and explanatory variable. Simulations are conducted to evaluate the performance of the proposed methodology. An example with real-world economy data is presented as an illustration.     

Assessing the relevance of higher education courses

The establishment of the European Higher Education Area has involved specifying lists of professional competencies that programs are expected to develop, and with this the need for procedures to measure how every course within a higher education program is aligned with the program's competencies. We propose an instrument for characterizing this alignment, a process that we call assessing the relevance of a course. Using information from the course syllabus (objectives, contents and assessment scheme), our instrument produces indicators for characterizing the syllabus in terms of a competence list and for assessing its coherence. Because assessment involves quality, the results obtained can also be used to revise and improve the course syllabus. We illustrate this process with an example of a methods course from a mathematics teacher education program at a Spanish university.     

Urban ecosystem Services in Latin America: mismatch between global concepts and regional realities?

Urban Ecosystems - Latin America and the Caribbean (LAC) is one of the most urbanized and biologically diverse regions in the world but is often characterized by weak environmental governance and...     

A feasibility approach for constructing combinatorial designs of circulant type

In this work, we propose an optimization approach for constructing various classes of circulant combinatorial designs that can be defined in terms of autocorrelation. The problem is formulated as a so-called feasibility problem having three sets, to which the Douglas–Rachford projection algorithm is applied. The approach is illustrated on three different classes of circulant combinatorial designs: circulant weighing matrices, D-optimal matrices of circulant type, and Hadamard matrices with two circulant cores. Furthermore, we explicitly construct two new circulant weighing matrices, a CW(126, 64) and a CW(198, 100), whose existence was previously marked as unresolved in the most recent version of Strassler’s table.     

Initiative in work teams: adaptation and validation of the Personal Initiative at Group Level Scale / Iniciativa en los equipos de trabajo: adaptación y validación de la Escala de Iniciativa Personal a nivel Grupal

In this study, we conceptualize personal initiative as a collective construct and adapt and validate a scale to evaluate it with a sample of 308 Spanish participants belonging to 91 work teams. Personal initiative at group level is a behavioural syndrome in which the team shows an approach to work that is self-initiated, proactive, persistent, capable of modifying the atmosphere and pro organization. As a predictive variable, we analysed the climate for initiative as well as personal initiative at group level. The resulting variables that were analysed referred to organization and team performance, with the team productivity and innovation as the criteria, analysing radical innovation. The scale has suitable psychometric properties. The results show that there is a relationship between the two predictive variables. Furthermore, personal initiative at group level is related to team productivity, while the climate for initiative is related to innovation.     

The impact of migration on the well-being of transnational families: new data from sending communities in Mexico

We present results from a new study of the effects of migration to the USA on the well-being of transnational families in high emigration communities within Mexico. Our survey measured the well-being of family members in a variety of domains: economic, health, education, and child development for a representative sample drawn from high migration municipalities. Compared to those with no recent emigrants to the USA, Mexican households sending non-caregivers to the USA appear to gain economically without contributing to problems faced by children. However, when family caregivers migrate to the USA, the remaining members in Mexico struggle to meet the family's needs and children are more vulnerable to educational, emotional, and health problems. Children in households where a caregiver migrated were more likely to have frequent illnesses (10% vs. 3%, p<0.0001), chronic illness (7% vs. 3%, p=0.011), emotional problems (10% vs. 4%, p=0.006), and behavioral problems (17% vs. 10%, p=0.018) compared with children in households where the migrant was not a caregiver. Research, policy, and program implications of these findings are discussed.     

Flexible objective Bayesian linear regression with applications in survival analysis

We study objective Bayesian inference for linear regression models with residual errors distributed according to the class of two-piece scale mixtures of normal distributions. These models allow for capturing departures from the usual assumption of normality of the errors in terms of heavy tails, asymmetry, and certain types of heteroscedasticity. We propose a general non-informative, scale-invariant, prior structure and provide sufficient conditions for the propriety of the posterior distribution of the model parameters, which cover cases when the response variables are censored. These results allow us to apply the proposed models in the context of survival analysis. This paper represents an extension to the Bayesian framework of the models proposed in [16]. We present a simulation study that shows good frequentist properties of the posterior credible intervals as well as point estimators associated to the proposed priors. We illustrate the performance of these models with real data in the context of survival analysis of cancer patients.