How to analyze percentile citation impact data meaningfully in bibliometrics: The statistical analysis of distributions, percentile rank classes, and top-cited papers

被引：56

作者：

Bornmann, Lutz ^{[1
]}

机构：

[1] Adm Headquarters Max Planck Soc, Div Sci & Innovat Studies, D-80539 Munich, Germany

来源：

JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY | 2013年 / 64卷 / 03期

关键词：

bibliometrics; PREDICTIVE-VALIDITY; INDICATORS; EXCELLENCE; COUNTS;

D O I：

10.1002/asi.22792

中图分类号：

TP [自动化技术、计算机技术];

学科分类号：

0812 ;

摘要：

According to current research in bibliometrics, percentiles (or percentile rank classes) are the most suitable method for normalizing the citation counts of individual publications in terms of the subject area, the document type, and the publication year. Up to now, bibliometric research has concerned itself primarily with the calculation of percentiles. This study suggests how percentiles (and percentile rank classes) can be analyzed meaningfully for an evaluation study. Publication sets from four universities are compared with each other to provide sample data. These suggestions take into account on the one hand the distribution of percentiles over the publications in the sets (universities here) and on the other hand concentrate on the range of publications with the highest citation impactthat is, the range that is usually of most interest in the evaluation of scientific performance.

引用

页码：587 / 595

页数：9

共 43 条

[11] Towards an ideal method of measuring research performance: Some comments to the Opthof and Leydesdorff (2010) paper [J].

Bornmann, Lutz .

JOURNAL OF INFORMETRICS, 2010, 4 (03) :441-443

[12]

Bornmann Lutz., 2008, Ethics in Science and Environmental Politics, V8, P93, DOI [10.3354/esep00084, DOI 10.3354/ESEP00084]

[13]

Bornmann Lutz, J AM SOC INFORM SCI

[14] Mapping knowledge domains: Characterizing PNAS [J].

Boyack, KW .

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2004, 101 :5192-5199

[15]

Cohen J., 1988, Statistical power analysis for the behavioral sciences, VSecond

[16] Speaking Stata: Graphing categorical and compositional data [J].

Cox, Nicholas J. .

STATA JOURNAL, 2004, 4 (02) :190-215

[17] An index to quantify an individual's scientific research output [J].

Hirsch, JE .

PROCEEDINGS OF THE NATIONAL ACADEMY OF SCIENCES OF THE UNITED STATES OF AMERICA, 2005, 102 (46) :16569-16572

[18]

Hosmer DW., 2000, Applied logistic regression, DOI DOI 10.1002/0471722146.CH4

[19]

Kohler U., 2009, Data analysis using Stata, V2nd

[20] Accounting for the uncertainty in the evaluation of percentile ranks [J].

Leydesdorff, Loet .

JOURNAL OF THE AMERICAN SOCIETY FOR INFORMATION SCIENCE AND TECHNOLOGY, 2012, 63 (11) :2349-2350

← 1 2 3 4 5 →