1,721,311 research outputs found
Bivariate meta-analysis of predictive values of diagnostic tests can be an alternative to bivariate meta-analysis of sensitivity and specificity
Full text linkOBJECTIVE: Meta-analysis of predictive values is usually discouraged because
these values are directly affected by disease prevalence, but sensitivity and
specificity sometimes show substantial heterogeneity as well. We propose a
bivariate random-effects logitnormal model for the meta-analysis of the positive
predictive value (PPV) and negative predictive value (NPV) of diagnostic tests.
STUDY DESIGN AND SETTING: Twenty-three meta-analyses of diagnostic accuracy were
reanalyzed. With separate models, we calculated summary estimates of the PPV and
NPV and summary estimates of sensitivity and specificity. We compared these
summary estimates, the goodness of fit of the two models, and the amount of
heterogeneity of both approaches.
RESULTS: There were no substantial differences in the goodness of fit or amount
of heterogeneity between both models. The median absolute difference between the
projected PPV and NPV from the summary estimates of sensitivity and specificity
and the summary estimates of PPV and NPV was 1% point (interquartile range, 0-2%
points).
CONCLUSION: A model for the meta-analysis of predictive values fitted the data
from a range of systematic reviews equally well as meta-analysis of sensitivity
and specificity. The choice for either model could be guided by considerations of
the design used in the primary studies and sources of heterogeneity
Effects of angiotensin converting enzyme inhibitors and angiotensin II receptor antagonists on mortality and renal outcomes in diabetic nephropathy: a systematic review
No full textOBJECTIVE: To evaluate the effects of angiotensin converting enzyme (ACE) inhibitors and angiotensin II receptor antagonists (AIIRAs) on renal outcomes and all cause mortality in patients with diabetic nephropathy. DATA SOURCES: Medline, Embase, the Cochrane controlled trials register, conference proceedings, and contact with investigators. STUDY SELECTION: Trials comparing ACE inhibitors or AIIRAs with placebo or with each other in patients with diabetic nephropathy. DATA EXTRACTION: Mortality, renal outcomes (end stage renal disease, doubling of serum creatinine concentration, prevention of progression of microalbuminuria to macroalbuminuria, remission of microalbuminuria), and quality of trials. DATA SYNTHESIS: 36 of 43 identified trials compared ACE inhibitors with placebo (4008 patients), four compared AIIRAs with placebo (3331 patients), and three compared ACE inhibitors with AIIRAs (206 patients). We obtained unpublished data for 11 trials. ACE inhibitors significantly reduced all cause mortality (relative risk 0.79, 95% confidence interval 0.63 to 0.99) compared with placebo but AIIRAs did not (0.99, 0.85 to 1.17), although baseline mortality was similar in the trials. Both agents had similar effects on renal outcomes. Reliable estimates of the unconfounded relative effects of ACE inhibitors compared with AIIRAs could not be obtained owing to small sample sizes. CONCLUSION: Although the survival benefits of ACE inhibitors for patients with diabetic nephropathy are known, the relative effects of ACE inhibitors and AIIRAs on survival are unknown owing to the lack of adequate head to head trials
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
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