1,720,983 research outputs found
Bayesian pooling versus sequential integration of small preclinical trials: a comparison within linear and nonlinear modeling frameworks
No full textBayesian sequential integration is an appealing approach in drug development, as it allows to recursively update posterior distributions as soon as new data become available, thus considerably reducing the computation time. However, preclinical trials are often characterized by small sample sizes, which may affect the estimation process during the first integration steps, particularly when complex PK-PD models are used. In this case, sequential integration would not be practicable, and trials should be pooled together. This work is aimed at comparing simple Bayesian pooling with sequential integration through a simulation study. The two techniques are compared under several scenarios using linear as well as nonlinear models. The results of our simulation study encourage the use of Bayesian sequential integration with linear models. However, in the case of nonlinear models several caveats arise. This paper outlines some important recommendations and precautions in that respect.La Gamba, F (corresponding author), Janssen Res & Dev, Dept Quantitat Sci, Beerse, Belgium; Hasselt Univ, Interuniv Inst Biostat & Stat Bioinformat, Diepenbeek, Belgium.
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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
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
Flexible Modeling Tools for Continuous Longitudinal Data
No full textIn this dissertation we have focussed on methods for modeling continuous, i.e., Gaussian, longitudinal data. We have shown that a flexible, rich set of tools is available for analyzing this type of data. In the repeated measures setting, each of the three model families, which were compared in detail in Chapter 4, model both the dependence of the response on the explanatory variables and the autocorrelation among the responses. Ignoring this correlation leads to incorrect inferences about the fixed-effect regression coefficients, and to a loss of efficiency, that is, less precise estimates. This point was illustrated in Chapter 5, where we were able to establish an additional treatment effect that had gone undetected in previous, simpler analyzes. By properly accounting for birdspecific effects, we gained power to assess the effect of treatment, underscoring the strength of the non-linear mixed modeling framework. In addition to a gain in efficiency, the modeling of within-subject correlation can also be of direct scientific interest. In Chapter 3, the correlation structure was examined to describe the persistence dimension of patients exhibiting persistent disturbing behavior (PDB). In Chapter 6, we focused on serial correlation and we proposed a spline-based approach to flexibly model the serial correlation function. Applying this method to data from a pre-clinical experiment in dementia, enabled us to show that a circadian pattern played a role in the mean structure, variance structure and the correlation structure simultaneously. However, as Davidian and Giltinan (1995, p. 330) mentioned, second moment behavior is inherently difficult to characterize, and this is especially true for correlation parameters. This also means that a substantial amount of information, i.e., a large dataset, is needed when drawing conclusions about the nature of the correlation structure. (Excerpt from Conclusion)
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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