1,720,995 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
Un test d'adéquation global pour la fonction de répartition conditionnelle
No full textBacro Jean-Noël Président du JuryBerlinet Alain ExaminateurDucharme Gilles Directeur de ThèseHarel Michel RapporteurSaracco Jérôme ExaminateurSarda Pascal RapporteurLet (X;Y) be a random real vector. Many statistical procedures allow to fit models to such data but this usually requires many assumptions that must somehow be validated before the model can be used with some degree of confidence. In this work, we propose a global test that can assess the validity of the supposed model by testing simultaneously all the hypotheses made about the model. This test is based on a quantity that embodies all the information about the joint behaviour of X and Y : the conditional distribution function F(y|x)=P(Ythe distribution function.Soient X et Y , deux variables aléatoires. De nombreuses procédures statistiques permettent d'ajuster un modèle à ces données dans le but d'expliquer Y à partir de X. La mise en place d'un tel modèle fait généralement appel à diverses hypothèses que l'on doit valider pour justifier son utilisation. Dans ce travail, on propose une approche globale où toutes les hypothèses faites pour asseoir ce modèle sont testées simultanément. Plus précisément, on construit un test basé sur une quantité qui permet de canaliser toute l'information liant X à Y : la fonction de répartition conditionnelle de Y sachant (X = x) définie par F(y|x)=P(Yvalidité si la distance entre ces deux quantités est trop grande. Dans un premier temps, on considère le cas où la fonction de répartition supposée est entièrement spécifiée et, dans ce contexte, on établit le comportement asymptotique du test. Dans la deuxième partie du travail, on généralise ce résultat au cas plus courant en pratique où le modèle supposé contient un certain nombre de paramètres inconnus. On étudie ensuite la puissance locale du test en déterminant son comportement asymptotique local sous des suites d'hypothèses contigües. Enfin, on propose un critère de choix de la fenêtre d'ajustement qui intervient lors de l'étape d'estimation polynômiale locale de la fonction de répartition conditionnelle
Nonparametric estimation of reference curves
No full textInternational audienceIn epidemiology, reference or standard curves are required to study fetal development in pregnancy. Values that lie outside the limits of these reference curves may indicate the presence of a disorder. Some classical empirical, parametric and semi-parametric methods, such as polynomial regression and LMS methods, are usually used to construct these curves. However, these classical methods build upon restrictive assumptions on estimated curves. The focus is on alternative nonparametric methods such as Nadaraya-Watson kernel estimation, local polynomial estimation, B-splines or cubic splines. The practical implementation of these methods to construct these curves requires working on smoothing parameters or choice of knots for the different types of nonparametric estimation. In particular, the optimal choice of these parameters is proposed. To fit these curves, we develop the R package quantCurves, an easy-to-use tool for practitioners, and a graphical interface to enable intuitive visualization of the results of the package
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
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