1,721,019 research outputs found
ASMOD 2018: Proceedings of the International Conference on Advances in Statistical Modelling of Ordinal Data
No full textThis volume collects the peer-reviewed contributions presented at the 2nd International Conference on “Advances in Statistical Modelling of Ordinal Data” - ASMOD 2018 - held at the Department of Political Sciences of the University of Naples Federico II (24-26 October 2018). The Conference brought together theoretical and applied statisticians to share the latest studies and developments in the field. In addition to the fundamental topic of latent structure analysis and modelling, the contributions in this volume cover a broad range of topics including measuring dissimilarity, clustering, robustness, CUB models, multivariate models, and permutation tests. The Conference featured six distinguished keynote speakers: Alan Agresti (University of Florida, USA), Brian Francis (Lancaster University, UK), Bettina Gruen (Johannes Kepler University Linz, Austria), Maria Kateri (RWTH Aachen, Germany), Elvezio Ronchetti (University of Geneva, Switzerland), Gerhard Tutz (Ludwig-Maximilians University of Munich, Germany). The volume includes 22 contributions from scholars that were accepted as full papers for inclusion in this edited volume after a blind review process of two anonymous referees
Discussion of “The class of cub models: statistical foundations, inferential issues and empirical evidence” by Domenico Piccolo and Rosaria Simone
No full textIn this paper we discuss the article “The class of CUB models: statistical foundations, inferential issues and empirical evidence” by Domenico Piccolo e Rosaria Simone. The main considered topic is the decision process that, according to the CUB paradigm, leads the respondent to express a rating about a latent trait on a given ordinal scale. We discuss a generalized formalization of this decision process, comprising the basic CUB model, some already existing extensions and possible future developments
On the choice of splitting rules for model-based trees for ordinal responses
No full textThe focus of the contribution is on the splitting criterion for model-based treeprocedure based on the class ofCUBmixture models for the analysis of ordinal scores. Theflexibility of the chosen modelling framework allows to select the splitting criterion to growthe tree according to the purposes of the study and the available data. In particular, theselection of variables yielding to the best partitioning results can be driven by fitting measuresor classical likelihood and deviance measures. The contribution proposes to investigate thefeatures of the available decision rules by a set of Montecarlo experiments, thus implicitlyfacing the problem of selecting the model-based tree to obtain an adequate and satisfyingoverview of response profiles
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
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
Modeling preferences: beyond the average effects
No full textPreference mapping are a collection of multivariate statistical techniques widely used by marketing and R&D divisions to understand which sensory characteristics drive consumer acceptance of goods. These techniques provide a perceptual map of the products based on the so-called sensory dimensions, on which the liking values for each consumer are regressed. This study proposes an innovative preference mapping based on the quantile regression. Using the quantile regression instead of the classical least squares regression allows to explore the whole distribution of the consumer preference. This permits to obtain additional information both at the individual consumer level, analyzing how the preference varies with respect to the different quantiles and at the general level, highlighting on the preference map consumers with homogeneous behaviors with respect to the different quantiles
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