Dataset Information

A new bibliometric index based on the shape of the citation distribution.

ABSTRACT: In order to improve the h-index in terms of its accuracy and sensitivity to the form of the citation distribution, we propose the new bibliometric index [symbol in text]. The basic idea is to define, for any author with a given number of citations, an "ideal" citation distribution which represents a benchmark in terms of number of papers and number of citations per publication, and to obtain an index which increases its value when the real citation distribution approaches its ideal form. The method is very general because the ideal distribution can be defined differently according to the main objective of the index. In this paper we propose to define it by a "squared-form" distribution: this is consistent with many popular bibliometric indices, which reach their maximum value when the distribution is basically a "square". This approach generally rewards the more regular and reliable researchers, and it seems to be especially suitable for dealing with common situations such as applications for academic positions. To show the advantages of the [symbol in text]-index some mathematical properties are proved and an application to real data is proposed.

SUBMITTER: Lando T

PROVIDER: S-EPMC4277364 | biostudies-literature | 2014

REPOSITORIES: biostudies-literature

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A new bibliometric index based on the shape of the citation distribution.

Lando Tommaso T Bertoli-Barsotti Lucio L

PloS one 20141226 12

In order to improve the h-index in terms of its accuracy and sensitivity to the form of the citation distribution, we propose the new bibliometric index [symbol in text]. The basic idea is to define, for any author with a given number of citations, an "ideal" citation distribution which represents a benchmark in terms of number of papers and number of citations per publication, and to obtain an index which increases its value when the real citation distribution approaches its ideal form. The met ...[more]

PMID: 25542026

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Project description:BackgroundObesity, typically quantified in terms of Body Mass Index (BMI) exceeding threshold values, is considered a leading cause of premature death worldwide. For given body size (BMI), it is recognized that risk is also affected by body shape, particularly as a marker of abdominal fat deposits. Waist circumference (WC) is used as a risk indicator supplementary to BMI, but the high correlation of WC with BMI makes it hard to isolate the added value of WC.Methods and findingsWe considered a USA population sample of 14,105 non-pregnant adults (age ≥ 18) from the National Health and Nutrition Examination Survey (NHANES) 1999-2004 with follow-up for mortality averaging 5 yr (828 deaths). We developed A Body Shape Index (ABSI) based on WC adjusted for height and weight: ABSI ≡ WC/(BMI(2/3)height(1/2)). ABSI had little correlation with height, weight, or BMI. Death rates increased approximately exponentially with above average baseline ABSI (overall regression coefficient of +33% per standard deviation of ABSI [95% confidence interval: +20%-+48%), whereas elevated death rates were found for both high and low values of BMI and WC. 22% (8%-41%) of the population mortality hazard was attributable to high ABSI, compared to 15% (3%-30%) for BMI and 15% (4%-29%) for WC. The association of death rate with ABSI held even when adjusted for other known risk factors including smoking, diabetes, blood pressure, and serum cholesterol. ABSI correlation with mortality hazard held across the range of age, sex, and BMI, and for both white and black ethnicities (but not for Mexican ethnicity), and was not weakened by excluding deaths from the first 3 yr of follow-up.ConclusionsBody shape, as measured by ABSI, appears to be a substantial risk factor for premature mortality in the general population derivable from basic clinical measurements. ABSI expresses the excess risk from high WC in a convenient form that is complementary to BMI and to other known risk factors.

Project description:BackgroundPublication metrics have been traditionally used to compare research productivity amongst academic faculty. However, traditional bibliometrics lack field-normalization and are often biased towards time-dependent publication factors. The National Institutes of Health (NIH) has developed a new, field-normalized, article-level metric, known as the "relative citation ratio" (RCR), that can be used to make accurate self, departmental, and cross-specialty comparisons of research productivity. This study evaluates the use of the RCR amongst academic orthopedic spine surgery faculty and analyzes physician factors associated with RCR values.MethodsA retrospective data analysis was performed using the iCite database for all fellowship trained orthopedic spine surgery (OSS) faculty associated with Accreditation Council for Graduate Medical Education (ACGME)-accredited orthopedic surgery residency program. Mean RCR, weighted RCR, and total publication count were compared by sex, career duration, academic rank, and presence of additional degrees. A value of 1.0 is the NIH-funded field-normalized standard. Student t-tests were used for two-group analyses whereas the analysis of variance tests (ANOVA) was used for between-group comparisons of three or more subgroups. Statistical significance was achieved at P < 0.05.ResultsA total of 502 academic OSS faculty members from 159 institutions were included in the analysis. Overall, OSS faculty were highly productive, with a median RCR of 1.62 (IQR 1.38-2.32) and a median weighted RCR of 68.98 (IQR 21.06-212.70). Advancing academic rank was associated with weighted RCR, career longevity was associated with mean RCR score, and male sex was associated with having increased mean and weighted RCR scores. All subgroups analyzed had an RCR value above 1.0.ConclusionsAcademic orthopedic spine surgery faculty produce impactful research as evidenced by the high median RCR relative to the standard value set by the NIH of 1.0. Our data can be used to evaluate research productivity in the orthopedic spine community.

Dataset Information

A new bibliometric index based on the shape of the citation distribution.

Publications

A new bibliometric index based on the shape of the citation distribution.

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