186,667 research outputs found
Code for: Credibility Assessment of Patient-Specific Computational Modeling using Patient-Specific Cardiac Modeling as an Exemplar
No full textCode for used to run the simulation studies in
Credibility Assessment of Patient-Specific Computational Modeling using Patient-Specific Cardiac Modeling as an Exemplar
S. Galappaththige, R. Gray, C. Costa, S. Niederer and P. Pathmanathan
(under submission
Bayesian tolerance intervals with probability matching priors / Dharini a/p Pathmanathan
No full textA review on statistical tolerance intervals shows that the derivation of two-sided tolerance intervals is far more challenging than that of their one-sided counterparts.
Much of the existing construction of two-sided tolerance intervals are through a numerical approach. This study addresses the problems of constructing two-sided tolerance intervals in balanced one-way random effects models and for a general family of distributions. The Bayesian tolerance interval developed by Ong and Mukerjee (2011) using probability matching priors (PMP) is compared via Monte Carlo simulation with the modified large sample (MLS) tolerance interval of Krishnamoorthy and Mathew (2009) for normal and non-normal experimental errors with respect to
coverage probabilities and expected widths. Data generated from normal and nonnormal experimental errors were studied to see the effects on the tolerance intervals since real data may not necessarily follow the normal distribution. Results show that the PMP tolerance interval appears to be less conservative for data with moderate and large number of classes while the MLS tolerance interval is preferable for smaller sample sizes. For the second part of the study, the PMP as well as frequentist two-sided tolerance intervals are constructed for a general family of parametric models.
Simulation studies show that the asymptotic results are well-reflected in finite sample sizes. The findings are then applied to real data. The results obtained in this research are a contribution to the area of statistical tolerance regions
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe 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
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe 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
No full textWe 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
Dr. Edward P. Wimberly, ITC, July 2011
No full textThis video is a conversation with Dr. Edward P. Wimberly. Dr. Wimberly talks about his book, "No Shame in Wesley's Gospel: A Twenty-First Century Pastoral Gospel". Brad Ost, AUC Woodruff Library, is the interviewer
Author Rights and Scholarly Publishing
No full textOriginally posted at
http://blog.library.gsu.edu/2014/10/24/author-rights-and-scholarly-publishing/</p
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