1,356,115 research outputs found
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Extension of the cross-classified multiple membership growth curve model for longitudinal data
No full texttextStudent mobility is a common phenomenon in longitudinal data in educational research. The characteristics of education longitudinal data create a problem for the conventional multilevel model. Grady and Beretvas (2010) introduced a cross-classified multiple membership growth curve (CCMM-GCM) model to handle Student mobility over time by capturing complex higher level clustering structure in the data. There are some limitations in the CCMM-GCM model. By creating dummy coded indicators for each measurement occasion, the new model can improve the accuracy and provides an easier and more flexible structure at the higher level. This study provides some support that the new model better fits a dataset than the CCMM-GCM modelStatistic
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe 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
No full text“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
No full textWe 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
No full textWe 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
Author, publisher and bookseller : a tripartite synergy in Nigerian book industry
No full textThis work is about the roles of Author, Publisher and Bookseller in Book development in
Nigeria. The paper started by delving into the history of Book Publishing in Nigeria after
which it proceeded by defining who an author, a publisher, and a bookseller is and
expatiated on the indispensable roles of these key actors in Nigerian Book Industry and in
the emerging Information Society. Furthermore, the various constraints to book
development were identified while the paper advised on how the Book Industry can be
further promoted in Nigeria. However, the paper concluded and made recommendations
on how the Book sector can help in enhancing scholarship in the country
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Random or fixed testlet effects : a comparison of two multilevel testlet models
No full texttextThis simulation study compared the performance of two multilevel measurement testlet (MMMT) models: Beretvas and Walker’s (2008) two-level MMMT model and Jiao, Wang, and Kamata’s (2005) three-level model. Several conditions were manipulated (including testlet length, sample size, and the pattern of the testlet effects) to assess the impact on the estimation of fixed and random effect parameters.
While testlets, in which items share the same stimulus, are common in educational tests, testlet item scores violate the assumption of local item independence (LID) underlying item response theory (IRT). Modeling LID has been widely discussed in previous studies (for example, Bradlow, Wainer, and Wang, 1999; Wang, Bradlow, and Wainer, 2002; Wang, Cheng, and Wilson, 2005). More recently, Jiao et al. (2005) proposed a three-level MMMT (MMMT-3r) in which items are modeled as nested within testlets (level two) and then testlets are nested with persons (level three).
Testlet effects are typically modeled as random in previous studies involving LID. However, item effects (difficulties) are commonly modeled as fixed under IRT models: that is, persons with the same ability level are assumed to have the same probability of answering an item correctly. Therefore, it is also important that a testlet effects model permit modeling of item effects as fixed. Moreover, modeling testlet effect as random implies testlets are being sampled from a larger population of testlets. However, as with item effects, researchers are typically more interested in a particular set of items or testlets that are being used in an assessment. Given the interest of the researcher or psychometrician using a testlet response model, it seems more useful to use a testlet response model that permits modeling testlets effects as fixed.
An alternative MMMT that permits modeling testlet effect as fixed and/or randomly varying has been proposed (Beretvas and Walker, 2008). The MMMT-2f and MMMT-2r models treat testlet effects as item-set-specific but not person-specific. However, no simulation has been conducted to assess how this proposed model performs.
The current study compared the performance of the MMMT-2f, MMMT-2r with that of the MMMT-3r. Results of the present simulation study showed that the MMMT-2r yielded the best parameter bias in estimation on fixed item effects, fixed testlet effects, and random testlet effects for conditions with nonzero equal pattern of random testlet effects’ variance even when the MMMMT-2r was not the generating model. However, random effects estimation did not perform well when unequal random testlet effects’ variances were generated. Fit indices did not perform well either as other studies have found. And it should be emphasized that model differences were of very little practical significance. From a modeling perspective, MMMT-2r does allow the greatest flexibility in terms of modeling testlet effects as fixed, random, or both.Educational Psycholog
The Thursday Murder Club: Launching a megabrand author - a publishing case study
No full textIn 2020, the Christmas book charts in the UK made headlines: Barack Obama’s eagerly awaited autobiography, The Promised Land, was beaten to the top spot by The Thursday Murder Club by Richard Osman, a debut cosy crime novel set in a retirement village. Not only did Osman’s book beat the former US president’s expected bestseller, it also broke records, becoming the fastest-selling debut crime novel of all time. Although Osman has a certain level of fame in the UK from his TV appearances on shows such as Pointless, his celebrity status does not entirely explain the novel’s huge sales. This article tracks the acquisition, publication, and promotion journey of The Thursday Murder Club in order to understand the industry and cultural context of its success and to interrogate the role of celebrity in the creation of author brands. The findings suggest that the unexpected scale of the success of the book owed to a number of factors, including in-depth editing by the novel’s agent, editor, and author to tighten up the plot, an extensive and strategic promotional campaign, the pandemic (which drove interest in the book’s genre and themes), and the quality of the writing. We find that the book’s success was accentuated by Osman’s celebrity status rather than being entirely reliant on it. This research adds to the growing scholarship on celebrity authorship by means of an in-depth case study and provides insight into the processes behind publishing a ‘celebrity’ book and launching a megabrand author
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Using IRT parameters as informative priors in second-order Bayesian latent growth modeling
No full textIn education, a wide variety of statistical methodologies are available to study change over time. For example, second-order latent growth models correct for item characteristics while estimating student-level growth. However, second-order latent growth models are difficult to estimate, with low convergence rates and high bias (Murphy, Beretvas, and Pituch, 2011). In attempting to correct this, I proposed and evaluated a new estimation method using the Kalman filter and informative priors for item parameters. This fully Bayesian estimation method was theoretically guaranteed to converge eventually, while informative parameters, theoretically justified within Item Response Theory, were hypothesized to reduce the mean squared error of parameter estimates. However, a simulation study found several scaling problems with the estimation method, and estimation using a real data set failed to converge. Discussion provides a few recommendations to correct these scaling problems.Educational Psycholog
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