1,720,956 research outputs found
The Determination of An Effective Smile
No full textThis research was supported by the Undergraduate Research Opportunities Program (UROP).Ruprecht, Mark, R.; Helwig, Nathaniel, E.. (2016). The Determination of An Effective Smile. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/180026
A Nonparametric Look at Self-Esteem Development by Gender and Socioeconomic Region
No full textWe examined self-esteem development across the lifespan from ages 10 to 80 using responses to the Rosenberg Self-Esteem Scale obtained over the World Wide Web between the years of 2011 and 2014. The dataset comprises a large and globally diverse sample of 45,185 individuals (53.2% non-U.S.) representing 171 countries from six continents. Using a nonparametric regression approach, we investigated whether the self-esteem developmental trajectory differed across gender and socioeconomic region.Ruprecht, Mark R.; Helwig, Nathaniel E.. (2016). A Nonparametric Look at Self-Esteem Development by Gender and Socioeconomic Region. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/185270
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
Adding bias to reduce variance in psychological results: A tutorial on penalized regression
Get PDFRegression models are commonly used in psychological research. In most studies, regression coefficients are estimated via maximum likelihood (ML) estimation. It is well-known that ML estimates have desirable large sample properties, but are prone to overfitting in small to moderate sized samples. In this paper, we discuss the benefits of using penalized regression, which is a form of penalized likelihood (PL) estimation. Informally, PL estimation can be understood as introducing bias to estimators for the purpose of reducing their variance, with the ultimate goal of providing better solutions. We focus on the Gaussian regression model, where ML and PL estimation reduce to ordinary least squares (OLS) and penalized least squares (PLS) estimation, respectively. We cover classic OLS and stepwise regression, as well as three popular penalized regression approaches: ridge regression, the lasso, and the elastic net. We compare the different penalties (or biases) imposed by each method, and discuss the resulting features each penalty encourages in the solution. To demonstrate the methods, we use an example where the goal is to predict a student's math exam performance from 30 potential predictors. Using a step-by-step tutorial with R code, we demonstrate how to (i) load and prepare the data for analysis, (ii) fit the OLS, stepwise, ridge, lasso, and elastic net models, (iii) extract and compare the model fitting results, and (iv) evaluate the performance of each method. Our example reveals that penalized regression methods can produce more accurate and more interpretable results than the classic OLS and stepwise regression solutions
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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