1,721,044 research outputs found
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
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Case Diagnostics in Categorical Factor Analysis
Get PDFCase diagnostics in categorical factor analysis include Mahalanobis distance-based statistics, which measure residual and leverage, and adaptations of existing influence diagnostics such as individual contribution to chi-square and generalized Cook’s distance which measure each case’s influence on statistical results. This dissertation uses two simulation studies to explore issues related to the use of case diagnostics in categorical factor analysis in order to assess the feasibility and utility of an iteratively reweighted least squares estimator for categorical factor analysis and structural equation modeling. In the first simulation, I used large data sets simulated according to a hypothesized model structure to examine the null distributions of Mahalanobis distance-based measures of residual and leverage in categorical factor analysis. Specifically, this study examined the validity of statistical cut-off values derived from continuous distributions in categorical factor analysis and assessed the differences between theoretical and empirical critical values in these models. In most conditions, the distributions of leverage and residual diagnostics in polytomous data, and of leverage diagnostics in dichotomous data, were similar enough to those in continuous data that existing critical values can safely be used to identify high-leverage cases. In contrast, residual diagnostics in dichotomous data had severely truncated distributions, a result which complicates the choice of critical value for identifying high-residual cases in residual analysis or down-weighting cases in robust estimation. In the second simulation, I examined the relationships between leverage, residual, and influence in categorical and continuous factor analysis and compared those relationships across continuous, polytomous, and dichotomous test conditions. Results were largely consistent between continuous and polytomous data but differed markedly in dichotomous data with high variability across dichotomous test conditions. Together, these findings reveal that, while categorical case diagnostics are well-behaved in polytomous tests under ideal conditions, these diagnostics can behave unpredictably in dichotomous data, and thus caution should be used in interpreting their values directly in dichotomous tests, whether as a means for screening for outliers or for down-weighting cases in robust estimation
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The Heteroscedastic Skew Graded Response Model: An Answer to the Non-Normality Predicament?
Get PDFAs item response theory models are more frequently applied to psychological assessment, understanding the ramifications of failing to account for non-normality is of utmost importance, especially, considering the likelihood of encountering traits that are non-normally distributed in the population (e.g., anxiety, depression). Previous research has established concerns with regard to bias in item parameter and trait score estimates when non-normality is ignored, and, as such developed models to aid in minimizing bias. Once such model is the heteroscedastic GRM with a skewed latent trait (HSGRM). This research provides an in-depth examination of the viability and utility of the HSGRM. Under various degrees of skew and heteroscedasticity, including extreme on both, this research addresses the consequences of ignoring non-normality and how to address it. A simulation study was conducted to evaluate the ability of the HSGRM to provide improved item parameter estimates, and recover the shape of the distribution (i.e., skew). Results support the HSGRM as a major improvement over the traditional GRM when faced with non-normality in data due to skew in the trait and heteroscedastic errors
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
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Iteration of Target Matrices in Exploratory Factor Analysis
Get PDFExploratory factor analysis (EFA) almost always involves two unique steps: 1) initial extraction of m orthogonal, "unrotated" factors from a covariance matrix, followed by 2) rotation of said factors to an interpretable structure. The present research is focused entirely on the second step, rotation; specifically, a new, semi-analytic rotation algorithm called iterated target rotation (ITR) is developed and tested. The goal of ITR is to improve upon basic target rotation (Hurley & Cattell, 1962) by automatically searching for a viable target matrix. Whereas basic target rotation requires a user to specify a target matrix a priori, ITR uses an iterative search procedure to find a viable (often ideal) target matrix. Using Monte Carlo simulation of raw data (N = 250, 500, and 1000), the performance of ITR was tested in simple, complex, and highly complex population factor structures. Further, two characteristics of the ITR algorithm itself were varied, resulting in the following four simulation condition variables: sample size (three conditions), complexity of population factor structure (four conditions), method for iterating solutions (three conditions), and method for beginning the iterations (seven conditions). Performance was defined as the ability to accurately recover a true factor structure, as measured by the root mean-square error (RMSE) between the ITR solution and the population structure. Results suggest that, with few exceptions, ITR performs well even in highly complex structures. Limitations and future directions are discussed, and one potential improvement on the target-iteration algorithm is tested preliminarily
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
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A Hybrid EM Algorithm for Linear Two-Way Interactions with Missing Data
Get PDFWe study an EM algorithm for estimating product-term regression models with missing data. The study of such problems in the likelihood tradition has thus far been restricted to an EM algorithm method using full numerical integration. However, under most missing data patterns, we show that this problem can be solved analytically, and numerical approximations are only needed under specific conditions. Thus we propose a hybrid EM algorithm, which uses analytic solutions when available and approximate solutions only when needed. The theoretical framework of our algorithm is described herein, along with two numerical experiments using both simulated and real data. We show that our algorithm confers higher accuracy to the estimation process, relative to the existing full numerical integration method. We conclude with a discussion of applications, extensions, and topics of further research
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