1,721,011 research outputs found
Likelihood-based Inference for Multivariate Regression Models using Synthetic Data
Full text linkLikelihood-based exact inference procedures are derived for the multivariate
regression model, for singly and multiply imputed synthetic data generated
via Posterior Predictive Sampling (PPS), via a newly proposed sampling method,
which will be called Fixed-Posterior Predictive Sampling (FPPS), and via Plug-in
sampling. By contemplating the single imputation case, the new developed procedures
fill the gap in the existing literature where inferential methods are only
available for multiple imputation and, by being based in exact distributions, it
may even be applied to cases where the sample size is small. Simulation studies
compare the results obtained from all the proposed exact inferential procedures
and also compare these with the results obtained from the adaptation of Reiter’s
combination rule to multiply imputed synthetic datasets. An application using
U.S. 2000 Current Population Survey data is discussed and measures of privacy
are presented and compared among all methods
Generation and Analysis of Synthetic Data for Privacy Protection Under the Multivariate Linear Regression Model
No full textIn this dissertations, the author derives likelihood-based exact inference for multiply imputed synthetic data under the multiple (p>1) univariate linear regression model and for singly and multiply imputed data under the multivariate linear regression model. In the former, the synthetic data are generated under plug-in sampling, where unknown parameters in the model are set equal to observed values of point estimators. In the latter, synthetic data are also generated under posterior predictive sampling where they are drawn from a posterior predictive distribution. Simulations are presented to confirm the methodology performs as the theory predicts and to evaluate privacy protection. Robustness studies are also given. In the final chapter, a new privacy protection method similar to bottom- and top-coding is proposed and its inferential properties explored
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
Dose-Response Modeling For Continuous Responses When Variance Is Not A Power Of The Mean
No full textIn the context of modeling dose-response data for continuous outcomes, a common procedure is to summarize the data based on sample means and sample variances, and fit a suitable model for the means, ?(d
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
SOME ASPECTS OF MULTIVARIATE QUALITY CONTROL CHARTS FOR DISPERSION
No full textIn multivariate quality control, we are looking for monitoring p characteristics simultaneously. Consider the variance covariance matrix. This matrix is symmetric and has the variances of each characteristic on the diagonal elements in the order X1, X2, ...,Xn. Now, consider that the order of these characteristics is really arbi- trary. If two characteristics were considered, for instance, height and weight, there are actually two ways to arrange the variancecovariance matrix. If three characteristics are considered, six dierent orderings of the variance covariance matrices are possible. In this thesis we will study the consequences of rearranging the variance covariance matrix under a multivariate quality control setting; using the method of decomposition of the variance covariance matrix proposed by Tang and Barnett(1996) for p = 2; 3 and 4
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