1,720,956 research outputs found
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
Statistical Methods for the Analysis of Data with a Lower Limit of Detection
Full text linkI denne oppgaven tar vi opp problemet med å analysere data målt på en kontinuerlig skala med en nedre deteksjonsgrense og null-inflasjon, for univariate, bivariate og longitudinelle data. Vi spesifiserer en sensurert binær blandingsmodell, som foreslått av Moulton og Halsey (\citeyear{moulton}). Modellen består av en diskret del som representerer andelen nuller i utvalget, og en kontinuerlig del for størrelsen på de positive responsene. Denne oppgaven gir en detaljert evaluering av den binære blandingsmodellen med intervallsensurering, sammenlignet med dens enklere varianter, Tobitmodellen og den usensurerte binære blandingsmodellen, samt å naivt bytte ut de sensurerte observasjonene med halvparten av deteksjonsgrensen. Vi simulerer data med varierende deteksjonsgrenser, parameterverdier og mengde nuller. De tre enklere modellene gir misvisende resultater ettersom de underliggende antakelsene brytes. Også den binære blandingsmodellen med intervallsensurering er upassende i enkelte scenario grunnet overparametrisering.
De fire kandidatmodellene blir anvendt på to datasett: (1) Konsentrasjoner av borrelioseantistoff i Sør-Trøndelag, og (2) data med cytokinkonsentrasjoner hos gravide kvinner med ulike autoimmune revmatiske sykdommer. Klyngestrukturen i de sistnevnte dataene grunnet repeterte målinger blir tatt hånd om ved å inkludere tilfeldige effekter i begge delene av blandingsmodellen.
I den første anvendelsen viser den binære blandingsmodellen med intervallsensurering seg å fungere godt til å estimere prevalensen av borrelioseinfeksjoner, men et lavt antall usensurerte observasjoner gjør at estimeringene blir svært usikre. Derfor kan enkel logistisk regresjon sies å være mer praktisk. I den andre anvendelsen ble tre cytokiner med ulik andel sensurerte observasjoner analysert. For alle tre viste de binære blandingsmodellene seg å være overlegne endelsmodellene. Signifikante forskjeller i tidsprofilene mellom diagnosene ble funnet i to av cytokinene.
I søket etter multivariate metoder for å analysere cytokindataene, ble tre bivariate modeller undersøkt; En bivariat Tobitmodell, en binær blandingsmodell og en firedels blandingsmodell. De to førstnevnte har vist lovende resultater i andre anvendelser, men ingen av modellene var adekvate for de aktuelle dataene.In this thesis, we address the problem of analyzing data measured on a continuous scale with a lower limit of detection and zero inflation, for univariate, bivariate, and longitudinal data. We specify a censored two-part mixture model, as proposed by \citet{moulton}. The model consists of one discrete part representing the proportion of the sample with zero values, and one continuous part for the magnitude of the response. This thesis provides a detailed evaluation using simulations of the two-part model with interval censoring compared to its simpler variants, the Tobit model and the uncensored two-part model, as well as naive substitution of the censored observations with half the detection limit. We simulate data scenarios with varying detection limits, parameter values, and proportions of zeroes. The three simpler models resulted in misleading parameter estimates as their assumptions were violated, but also the censored two-part model was inappropriate in some scenarios due to over-parameterization.
The four candidate models are applied to two datasets: (1) Borrelia antibody concentrations in Sør-Trøndelag, and (2) data on cytokine concentrations in pregnant women with different autoimmune rheumatic diseases. The cluster structure of the data due to repeated measurements in the latter application is accounted for by including random effects in both parts of the model.
In the former application, the two-part model with interval censoring is demonstrated to work well for estimating the prevalence of borrelia infections, but the high amount of uncertainty due to a low number of uncensored observations makes the simpler logistic regression more feasible in this particular case. In the second application, three cytokines with different proportions of censored samples are analyzed. For all three, the binary mixture models are found to be superior to the one-part models. With the two-part models, significant differences in the time profiles between the diagnostic groups were found in two of the cytokines.
In a search for multivariate methods for analysis of the cytokine data, we specified three bivariate models; A bivariate Tobit model, a two-part mixture model, and a four-part mixture model. The two first-mentioned have shown promise in other applications, but none of the models were suitable for the problem at hand
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
Statistical Methods for the Analysis of Data with a Lower Limit of Detection
No full textI denne oppgaven tar vi opp problemet med å analysere data målt på en kontinuerlig skala med en nedre deteksjonsgrense og null-inflasjon, for univariate, bivariate og longitudinelle data. Vi spesifiserer en sensurert binær blandingsmodell, som foreslått av Moulton og Halsey (\citeyear{moulton}). Modellen består av en diskret del som representerer andelen nuller i utvalget, og en kontinuerlig del for størrelsen på de positive responsene. Denne oppgaven gir en detaljert evaluering av den binære blandingsmodellen med intervallsensurering, sammenlignet med dens enklere varianter, Tobitmodellen og den usensurerte binære blandingsmodellen, samt å naivt bytte ut de sensurerte observasjonene med halvparten av deteksjonsgrensen. Vi simulerer data med varierende deteksjonsgrenser, parameterverdier og mengde nuller. De tre enklere modellene gir misvisende resultater ettersom de underliggende antakelsene brytes. Også den binære blandingsmodellen med intervallsensurering er upassende i enkelte scenario grunnet overparametrisering.
De fire kandidatmodellene blir anvendt på to datasett: (1) Konsentrasjoner av borrelioseantistoff i Sør-Trøndelag, og (2) data med cytokinkonsentrasjoner hos gravide kvinner med ulike autoimmune revmatiske sykdommer. Klyngestrukturen i de sistnevnte dataene grunnet repeterte målinger blir tatt hånd om ved å inkludere tilfeldige effekter i begge delene av blandingsmodellen.
I den første anvendelsen viser den binære blandingsmodellen med intervallsensurering seg å fungere godt til å estimere prevalensen av borrelioseinfeksjoner, men et lavt antall usensurerte observasjoner gjør at estimeringene blir svært usikre. Derfor kan enkel logistisk regresjon sies å være mer praktisk. I den andre anvendelsen ble tre cytokiner med ulik andel sensurerte observasjoner analysert. For alle tre viste de binære blandingsmodellene seg å være overlegne endelsmodellene. Signifikante forskjeller i tidsprofilene mellom diagnosene ble funnet i to av cytokinene.
I søket etter multivariate metoder for å analysere cytokindataene, ble tre bivariate modeller undersøkt; En bivariat Tobitmodell, en binær blandingsmodell og en firedels blandingsmodell. De to førstnevnte har vist lovende resultater i andre anvendelser, men ingen av modellene var adekvate for de aktuelle dataene
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
- …
