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Radiol Med. 2018 Jul;123(7):524-534. doi: 10.1007/s11547-018-0870-y. Epub 2018 Mar 5.

Eigenfactor score and alternative bibliometrics surpass the impact factor in a 2-years ahead annual-citation calculation: a linear mixed design model analysis of Radiology, Nuclear Medicine and Medical Imaging journals.

Author information

1
Directorate of Research. Hospital General de Mexico "Dr. Eduardo Liceaga", Dr. Balmis 148 Street, Col. Doctores, Del. Cuauhtemoc, 06726, Mexico City, Mexico. ernest.roldan@usa.net.
2
Magnetic Resonance Unit, Medica Sur Clinic and Foundation, Mexico City, Mexico.
3
Departamento de Neuroquimica, Instituto Nacional de Neurologia y Neurocirugia, Mexico City, Mexico.

Abstract

INTRODUCTION:

Because we believe the journal selection before a manuscript submission deserves further investigation in each medical specialty, we aimed to evaluate the predictive ability of seven bibliometrics in the Radiology, Nuclear Medicine and Medical Imaging category of the Web of Knowledge to calculate total citations over a 7-year period.

METHODS:

A linear mixed effects design using random slopes and intercepts were performed on bibliometrics corresponding to 124 journals from 2007 to 2011, with their corresponding citations from 2009 to 2013, which appeared in the Journal Citations Report Science Edition.

RESULTS:

The Eigenfactor Score, Article Influence Score, Cited Half-life, 5-years impact factor and Number of Articles are significant predictors of 2-year-ahead total citations (p ≤ 0.010 for all variables). The impact factor and Immediacy Index are not significant predictors. There was a significant global effect size (R2 = 0.934; p < 0.001), which yielded a total variance of 93.4%.

CONCLUSIONS:

Our findings support researchers' decision to stop the misuse of IF alone to evaluate journals. Radiologists and other researchers should review journal's bibliometrics for their decision-making during the manuscript submission phase. A re-ranking of journals using Eigenfactor Score, Article Influence Score, and Cited Half-life provides a better assessment of their significance and importance in particular disciplines.

KEYWORDS:

Algorithms; Bibliometrics; Citation; Impact factor; Predictive value; Self-evaluation

PMID:
29508240
DOI:
10.1007/s11547-018-0870-y
[Indexed for MEDLINE]

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