1,720,998 research outputs found
A Predicitive Approach to the Bayesian Design Problem with Application to Normal Regression Models
Full text link1 online resource (PDF, 20 pages)Eaton, Morris; Giovagnoli, Alessandra; Sebastiani, Paola. (1994). A Predicitive Approach to the Bayesian Design Problem with Application to Normal Regression Models. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/199620
A new 'biased coin design' for the sequential allocation of two treatments
No full textEfron's (1971) Biased Coin Design is a well-known randomization technique that helps neutralize selection bias in sequential clinical trials for comparing treatments, while keeping the experiment fairly balanced. Extensions of the BCD have been proposed by several authors, who have focused mainly on the large sample properties of their designs. We modify Efron's procedure by introducing an Adjustable Biased Coin Design (ABCD), more flexible than his. We compare it to other existing coin designs; in terms of balance and lack of predictability, its performance for small samples appears in many cases to be an improvement with respect to the other sequential randomized allocation procedure
The analysis of contingency tables with ordinal data: an application to monitoring antibiotic resistance
No full textRationalization of antibiotic therapy in the management of infectious diseases is helped by a knowledge of the patterns of sensitivity and resistance of bacteria to antibiotics and their possible changes both in time and from one hospital unit to another. In this paper we present the results regarding the sensitivities of several groups of bacteria and different Units of the S.Orsola-Malpighi Hospital of
Bologna in the period 1995-1997. We apply recent methods of analysis of ordinal contingency tables that rely on stochastic ordering of the rows to test the assumption that a decrease (or increase) in sensitivity of bacteria to specific antibiotics has taken place against the alternative that no such thing has happened. In most cases the results seem to indicate an increase in sensitivity rather than what was expected, namely the opposite
Optimal Experiments in the presence of a learning effect: a problem suggested by software production
No full textIn software engineering empirical comparisons of different ways of writing computer code are often made. This leads to the need for planned experimentation and has recently established a new area of application of DoE. This paper is motivated by an experiment on the production of multimedia services on the web, performed at the Telecom Research Centre in Turin, where two different ways of developing code, with or without a framework, were compared. As the experiment progresses, the programmer’s performance improves as he/she undergoes a learning process; this must be taken into account as it may affect the outcome of the trial. In this paper we discuss statistical models and D-optimal plans for such experiments and indicate some heuristics which allow a much speedier search for the optimum. Solutions differ according to whether we assume that the learning process depends or not on the treatments
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
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