5 resultados para Discrete Regression and Qualitative Choice Models
em Université de Lausanne, Switzerland
Resumo:
Abstract: This article presents both a brief systemic intervention method (IBS) consisting in 6 sessions developed in an ambulatory service for couples and families, and two research projects done in collaboration with the Institute for Psychotherapy of the University of Lausanne. The first project is quantitative and it aims at evaluating the effectiveness of ISB. One of its main feature is that outcomes are assessed at different levels of individual and family functioning: 1) symptoms and individual functioning; 2) quality of marital relationship; 3) parental and co-parental relationships; 4) familial relationships. The second project is a qualitative case study about a marital therapy which identifies and analyses significant moments of the therapeutic process from the patients' perspective. Methodology was largely inspired by Daniel Stem's work about "moments of meeting" in psychotherapy. Results show that patients' theories about relationship and change are important elements that deepen our understanding of the change process in couple and family therapy. The interest of associating clinicians and researchers for the development and validation of a new clinical model is discussed.
Resumo:
The algorithmic approach to data modelling has developed rapidly these last years, in particular methods based on data mining and machine learning have been used in a growing number of applications. These methods follow a data-driven methodology, aiming at providing the best possible generalization and predictive abilities instead of concentrating on the properties of the data model. One of the most successful groups of such methods is known as Support Vector algorithms. Following the fruitful developments in applying Support Vector algorithms to spatial data, this paper introduces a new extension of the traditional support vector regression (SVR) algorithm. This extension allows for the simultaneous modelling of environmental data at several spatial scales. The joint influence of environmental processes presenting different patterns at different scales is here learned automatically from data, providing the optimum mixture of short and large-scale models. The method is adaptive to the spatial scale of the data. With this advantage, it can provide efficient means to model local anomalies that may typically arise in situations at an early phase of an environmental emergency. However, the proposed approach still requires some prior knowledge on the possible existence of such short-scale patterns. This is a possible limitation of the method for its implementation in early warning systems. The purpose of this paper is to present the multi-scale SVR model and to illustrate its use with an application to the mapping of Cs137 activity given the measurements taken in the region of Briansk following the Chernobyl accident.
Resumo:
Recent literature evidences differential associations of personal and general just-world beliefs with constructs in the interpersonal domain. In line with this research, we examine the respective relationships of each just-world belief with the Five-Factor and the HEXACO models of personality in one representative sample of the working population of Switzerland and one sample of the general US population, respectively. One suppressor effect was observed in both samples: Neuroticism and emotionality was positively associated with general just-world belief, but only after controlling for personal just-world belief. In addition, agreeableness was positively and honesty-humility negatively associated with general just-world belief but unrelated to personal just-world belief. Conscientiousness was consistently unrelated to any of the just-world belief and extraversion and openness to experience revealed unstable coefficients across studies. We discuss these points in light of just-world theory and their implications for future research taking both dimensions into account.