1,721,236 research outputs found
IDENTIFICAZIONE DEGLI ASSI FATTORIALI INFORMATIVI NELL'ANALISI DELLE COMPONENTI PRINCIPALI
No full textDetermining how many factors to retain as expression of an underlying structure is an important topic in principal component analysis (PCA). With this aim, different empirical criteria are usually adopted, such as to retain all eigenvalues higher than 1 (Kaiser-Guttman rule), or the first eigenvalues totalling a prefixed amount of explained variance, or higher than a prefixed threshold (broken-stick method), or those eigenvalues that depart from the straight line on which tend to lie all the other eigenvalues (scree plot). Yet, these rules often have weak theoretical bases and not always are appropriately applied. Facing this problem from a mathematical-analytical point of view by finding the distribution of the eigenvalues of sampling correlation matrices is a hard task, and most studies report results which are valid only asymptotically or under specific assumptions. There is a need to generalize the method, also to deal with real and possibly small datasets.
The aim of this thesis was to model the decision thresholds for the eigenvalue distribution as a function of number of variables (k) and sample size (n), under the assumptions that no latent factors exist and variables are standard-normally distributed. Two methods were taken into consideration: a direct and an indirect method. Through a simulation, data were generated for 70 different settings, obtained combining 7 different values for n (75, 150, 300, 600, 1200, 2400, 4800) with 10 different values for k (6, 12, 18, 24, 30, 36, 42, 48, 60). All variables were generated as independent and standard-normally distributed. The distribution of the first 4 eigenvalues of the correlation matrix was considered and the values of the 95th centiles were computed. For each setting, PCA was applied to 6001 independent samples. It was shown that there is a positive correlation between couples of consecutive eigenvalues, and that this correlation increases as k increases and, to a lesser extent, as n increases. It is expected that this pattern also persists when latent factors are present.
With the direct method, the observed 95th centile of the distribution of the first 4 eigenvalues could be predicted as a function of k and n by a nonlinear model with 7 parameters. With the indirect method, we normalized the distribution of the first 4 eigenvalues through a 3-parameter Box-Cox transformation. The parameters of the Box-Cox transformation were then expressed as functions of k and n, and used to predict the 95th centile.
Both methods appeared to accurately predict the value of the 95th centile. For the first eigenvalue, the mean of the absolute difference between type I error risk associated with the observed and the predicted thresholds is 3‰ for the direct method and 5‰ for the indirect method. The latter method has the additional advantage of providing any computed eigenvalue with its probability of occurrence under the null hypothesis. The number of samples generated in this study is large enough to obtain highly precise estimates of the type I error risk as regards the 1st eigenvalue. The reliability of the estimates is lower for the 2nd and, a fortiori, the 3rd and 4th eigenvalue.
Further research in this field should focus on how and to what extent the distribution of the eigenvalues of sample correlation matrices depends on the shape of the parent distribution (e.g. skewed, leptokurtic, multimodal), and on the possible extension of the predicting functions to the case where latent factors exist, by including a parameter that takes into account the variance explained by these factors
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
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
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
Author-wise bibliometric analysis based on entropy.
No full textAuthor-wise bibliometric analysis based on entropy.</p
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