1,720,958 research outputs found
Wild Bootstrap for Counting Process-Based Statistics
Get PDFThe wild bootstrap is a popular resampling method in the context of
time-to-event data analyses. Previous works established the large sample
properties of it for applications to different estimators and test statistics.
It can be used to justify the accuracy of inference procedures such as
hypothesis tests or time-simultaneous confidence bands. This paper consists of
two parts: in Part~I, a general framework is developed in which the large
sample properties are established in a unified way by using martingale
structures. The framework includes most of the well-known non- and
semiparametric statistical methods in time-to-event analysis and parametric
approaches. In Part II, the Fine-Gray proportional sub-hazards model
exemplifies the theory for inference on cumulative incidence functions given
the covariates. The model falls within the framework if the data are
censoring-complete. A simulation study demonstrates the reliability of the
method and an application to a data set about hospital-acquired infections
illustrates the statistical procedure.Comment: 2 parts, 115 pages, 2 figures, 13 table
A non-Markovian model for cell population growth: speed of convergence and central limit theorem
No full textIn De Gunst (1989) a stochastic model was developed for the growth of a batch culture of plant cells. In this paper the mathematical properties of the model are considered. We investigate the asymptotic behaviour of the population growth as predicted by the model when the initial cell number of population members tends to infinity. In particular it is shown that the total cell number, which is a non-Markovian counting process, converges almost surely, uniformly on the real line to a non-random function and the rate of convergence is established. Moreover, a central limit theorem is proved. Computer simulations illustrate the behaviour of the process. The model is graphically compared with experimental data.stochastic model population growth non-Markovian counting process almost sure converegence rate of convergence central limit theorem
Inference via Wild Bootstrap and Multiple Imputation under Fine-Gray Models with Incomplete Data
Get PDFFine-Gray models specify the subdistribution hazards for one out of multiple
competing risks to be proportional. The estimators of parameters and cumulative
incidence functions under Fine-Gray models have a simpler structure when data
are censoring-complete than when they are more generally incomplete. This paper
considers the case of incomplete data but it exploits the above-mentioned
simpler estimator structure for which there exists a wild bootstrap approach
for inferential purposes. The present idea is to link the methodology under
censoring-completeness with the more general right-censoring regime with the
help of multiple imputation. In a simulation study, this approach is compared
to the estimation procedure proposed in the original paper by Fine and Gray
when it is combined with a bootstrap approach. An application to a data set
about hospital-acquired infections illustrates the method.Comment: 32 pages, 2 figures, 1 tabl
Going Beyond Counting First Authors in Author Co-citation Analysis
Get PDFThe 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
Get PDF“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
Get PDFWe 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
Get PDFWe 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
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