1,720,972 research outputs found
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
Testmetoder for identifisering av publikasjonsbias i metaanalyser
Full text linkTestmetoder for identifisering av publikasjonsbias i metaanalyser
Family-based genetic association models
Full text linkThe high heritability and recurrence rates observed for several complex diseases justify the search for genetic risk factors. However, despite decades of intense and extensive research, the underlying genetic basis of most complex traits has not been fully deciphered. This unexplained genetic etiology underscores the need to examine etiologic disease mechanisms other than simple genetic effects alone, such as the effect of maternal genes or the effect of parental origin. Additionally, since genome-wide association studies (GWAS) are commonly underpowered due to the large number of single-nucleotide polymorphisms being tested, poorly designed and inadequately powered studies that are unable to capture most of the genetic variants underlying a trait might also contribute to the unexplained genetic etiology. Family-based study designs have been introduced specifically for studies of genetic risk factors. The main study unit is the case-parent triad design, which involves genotyping cases (affected offspring) and both their biological parents. However, a variety of other child-parent configurations and population-based study designs are also amenable to genetic association studies, including (but not limited to) cases in combination with unrelated controls, case-mother dyads, and case-parent triads in combination with unrelated controls or control-parent triads. Large clinical and population-based biobanks and national health registries have created unique opportunities for genetic, epidemiological, and clinical research worldwide. Nonetheless, there is currently a lack of flexible models that accommodate family structure in data. Models that incorporate non-standard genetic effects, such as maternal effects and parent-of-origin effects, are warranted. Moreover, joint models that integrate genetic, environmental, and epigenetic risk factors are needed to elucidate their combined effect on disease. This thesis focuses on models for analyzing GWAS data for binary disease traits as well as methods for maximizing the statistical power of such studies, allowing for a broad range of child-parent configurations in the calculations. Using maximum likelihood estimation in a log-linear model, we developed new methodology to detect parent-of-origin-environment interactions, a possible mechanism contributing to disease susceptibility that has not yet been sufficiently explored. The approach has been implemented in our R package Haplin. In the Haplin framework, we also developed an extensive setup for power and sample size calculations, both through analytic approximations and Monte Carlo simulations, which is essential not only in study planning but also in understanding and interpreting statistical findings. Within the power calculation module, we also implemented a relative efficiency calculator. Relative efficiency measures allow a more informative and general design comparison than straightforward and standard power analyses. We aimed to optimize the study design in genetic association studies given the constraints of available resources, i.e., maximize the statistical power using the least sample collection and genotyping cost
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
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
koamabayili/VECTRON-author-checklist: VECTRON author checklist
No full textWe have done our best to complete the author checklist relating to the use of animals in the hut study. Note that the objective for the hut study was to evaluate the IRS treatment applications for residual efficacy against Anopheles mosquitoes, including the local An. coluzzii mosquito population. Cows were only used to attract mosquitoes into the huts and no tests were carried out directly on the cows. The author checklist is intended for use with studies where experiments are carried out on animals, which is why we have had such difficulty in completing this for the hut study, as many of the questions do not relate to how the cows were used
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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