1,720,959 research outputs found
Robust confidence intervals for meta-regression with interaction effects
No full textAbstract Meta-analysis is an important statistical technique for synthesizing the results of multiple studies regarding the same or closely related research question. So-called meta-regression extends meta-analysis models by accounting for study-level covariates. Mixed-effects meta-regression models provide a powerful tool for evidence synthesis, by appropriately accounting for between-study heterogeneity. In fact, modelling the study effect in terms of random effects and moderators not only allows to examine the impact of the moderators, but often leads to more accurate estimates of the involved parameters. Nevertheless, due to the often small number of studies on a specific research topic, interactions are often neglected in meta-regression. In this work we consider the research questions (i) how moderator interactions influence inference in mixed-effects meta-regression models and (ii) whether some inference methods are more reliable than others. Here we review robust methods for confidence intervals in meta-regression models including interaction effects. These methods are based on the application of robust sandwich estimators of Hartung-Knapp-Sidik-Jonkman ( HKSJ ) or heteroscedasticity-consistent ( HC )-type for estimating the variance-covariance matrix of the vector of model coefficients. Furthermore, we compare different versions of these robust estimators in an extensive simulation study. We thereby investigate coverage and width of seven different confidence intervals under varying conditions. Our simulation study shows that the coverage rates as well as the interval widths of the parameter estimates are only slightly affected by adjustment of the parameters. It also turned out that using the Satterthwaite approximation for the degrees of freedom seems to be advantageous for accurate coverage rates. In addition, different to previous analyses for simpler models, the HKSJ -estimator shows a worse performance in this more complex setting compared to some of the HC -estimators.German Research Foundation 501100001659Technische Universität Dortmund 50110001637
The consequences of neglected confounding and interactions in mixed‐effects meta‐regression: An illustrative example
No full textDeutsche Forschungsgemeinschaft https://doi.org/10.13039/50110000165
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
Robust covariance estimation in mixed-effects meta-regression models
Full text linkIn this PhD thesis we consider robust (sandwich) variance-covariance matrix estimators in the context of univariate and multivariate meta-analysis and meta-regression. The underlying model is the classical mixed-effects meta-regression model. Our goal is to enable valid statistical inference for the model coefficients. Specifically, we employ heteroscedasticity consistent (HC) and cluster-robust (CR) sandwich estimators in the univariate and multivariate setting. A key aim is to provide better small sample solutions for meta-analytic research and application. Tests based on the original formulations of these estimators are known to produce highly liberal results, especially when the number of studies is small. We therefore transfer results for improved sandwich estimation by Cribari-Neto and Zarkos (2004) to the meta-analytic context. We prove the asymptotic equivalence of HC estimators and compare them with commonly suggested techniques such as the Knapp-Hartung (KH) method or standard plugin covariance matrix estimation in extensive simulation studies. The new versions of HC estimators considerably outperform their older counterparts, especially in small samples, achieving comparable results to the KH method. In a slight excursion, we focus on constructing confidence regions for (Pearson) correlation coefficients as the main effect of interest in a random-effects meta-analysis. We develop a beta-distribution model for generating data in our simulations in addition to the commonly used truncated normal distribution model. We utilize different variance estimation approaches such as HC estimators, the KH method and a wild bootstrap approach in combination with the Fisher-z transformation and an integral z-to-r back-transformation to construct confidence regions. In simulation studies, our novel proposals improve coverage over the Hedges-Olkin-Vevea-z approach and Hunter-Schmidt approaches, enabling reliable inference for a greater range of true correlations. Finally, we extend our results for the HC estimators to construct CR sandwich estimators for multivariate meta-regression. The aim is to achieve valid inference for the model coefficients, based on Wald-type statistics, even in small samples. Our simulations show that previously suggested CR estimators such as the bias reduced linearization approach, can have unsatisfactory small sample performance for bivariate meta-regression. Furthermore, they show that the Hotelling’s T^2-test suggested by Tipton and Pustejovsky (2015) can yield negative estimates for the degrees of freedom when the number of studies is small. We suggest an adjustment to the classical F -test, truncating the denominator degrees of freedom at two. Our CR extensions, using only the diagonal elements of the hat matrix to adjust residuals, improve coverage considerably in small samples. We focus on the bivariate case in our simulations, but the discussed approaches can also be applied more generally. We analyze both small and large sample behavior of all considered tests / confidence regions in extensive simulation studies. Furthermore, we apply the discussed approaches in real life datasets from psychometric and medical research
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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