1,721,024 research outputs found
Using graphical chain models to analyze differences in structural correlates of undernutrition in Benin and Bangladesh
No full textUndernutrition among children is one of the most important health problems in developing countries. In order to understand the complex pathways affecting undernutrition which is crucial for policy interventions, one needs to explicitly model the dependence chain of immediate, intermediate, and underlying factors affecting undernutrition. Graphical chain models are used here to investigate the determinants of undernutrition in Benin and Bangladesh. While the dependence chain affecting undernutrition contains many common elements, the influence of demographic, cultural, and socioeconomic factors seems to have stronger direct and indirect influences in Benin than in Bangladesh, where many socioeconomic and gender related factors have a more direct influence on undernutrition
Undernutrition in Benin - an analysis based on graphical models
No full textUndernutrition is one of the most important health problems in developing countries. Examining its determinants implies the investigation of a complex association structure including a large number of potential influence variables and different types of influences. A recently developed statistical technique to cope with such situations are graphical chain models. In this paper, this approach is used to investigate the determinants of undernutrition in Benin (West Africa). Since this method also reveals indirect influences, interesting insight is gained into the association structure of all variables incorporated. The analysis identifies mother's education, socioeconomic status, and religion as three variables with particularly strong direct and indirect linkages to undernutrition
P1.03: Revealing different structural components of malnutrition in Benin and Bangladesh by graphical chain models
No full textPerception of Sleep and Dreams in Alcohol-Dependent Patients during Detoxication and Abstinence
No full textAims: This study aims to investigate sleep quality and the subjective dream experience in alcohol-dependent patients during withdrawal and abstinence compared with healthy controls. Methods: Thirty-seven patients with alcohol dependency and 35 healthy control subjects were asked to fill in several questionnaires and to give information about their subjective sleep and dream experiences. Twelve patients participated in a follow-up interview 4 weeks later. Results: Sleep quality is impaired in alcohol-dependent patients during detoxication, and the subjective dream experience is more negatively toned compared with healthy controls. Both sleep quality and dream experience improves slightly after 4 weeks of abstinence. Patients with alcohol dependency during withdrawal and abstinence dream significantly more often about alcohol. However, none of the abstinent alcohol-dependent patients dreamt about alcohol during withdrawal. Conclusions: This study shows that the subjective sleep and dream quality is strongly impaired in patients with alcohol dependency. Differences in the dream experience between alcohol-dependent patients and healthy controls are in accordance with the continuity hypotheses of dreaming. The hypothesis of dreaming about alcohol as a compensatory effect, however, could not be confirmed
Der Conditional Synergy Index --Ein Maß zur Bestimmung einer Gen-Gen-Interaktion basierend auf graphischen Modellen
No full textIn genetic studies of complex diseases, it is important to identify and qualify gene-gene interactions. Interaction is often defined as deviance from genetic additive effects. But this statistical definition needs not to reflect the genes' biological interactions. I propose a new method to detect gene-gene interaction that exploits the concept of synergy and antagonism, which is said to capture biological relationships. The conditional synergy index (CSI) classifies and quantifies interaction on the penetrance scale. The general theory under two-locus disease models is developed. The index assumes a cohort design and genotypes to be dichotomized into risk-genotypes (exposed) and non-risk-genotypes (unexposed) but it does not assume the loci to be in linkage equilibrium. In simulation studies the performance of the CSI, its estimator and variance is investigated and compared to the performance of various epidemiological interaction measure like e.g. Rothman's syngergy index and to appropriate bootstrap estimators. The results exhibit that in contrast to common interaction measures, only the CSI is adequat to detect interaction on the penetrance scale. However, the proposed estimator of the CSI shows a slow convergence
The Conditional Synergy Index --A measure based on graphical models to assess gene-gene interaction
No full textIn genetic studies of complex diseases, it is important to identify and qualify gene-gene interactions. Interaction is often defined as deviance from genetic additive effects. But this statistical definition needs not to reflect the genes' biological interactions. I propose a new method to detect gene-gene interaction that exploits the concept of synergy and antagonism, which is said to capture biological relationships. The conditional synergy index (CSI) classifies and quantifies interaction on the penetrance scale. The general theory under two-locus disease models is developed. The index assumes a cohort design and genotypes to be dichotomized into risk-genotypes (exposed) and non-risk-genotypes (unexposed) but it does not assume the loci to be in linkage equilibrium. In simulation studies the performance of the CSI, its estimator and variance is investigated and compared to the performance of various epidemiological interaction measure like e.g. Rothman's syngergy index and to appropriate bootstrap estimators. The results exhibit that in contrast to common interaction measures, only the CSI is adequat to detect interaction on the penetrance scale. However, the proposed estimator of the CSI shows a slow convergence
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
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