Comparison of number of citations to full original articles versus brief reports

Mavros, Michael N.; Bardakas, Vangelis; Rafailidis, Petros I.; Sardi, Thalia A.; Demetriou, Elena; Falagas, Matthew E.

doi:10.1007/s11192-012-0752-3

Cited by 7 publications

(6 citation statements)

References 6 publications

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“…In the field of Astronomy and Astrophysics, lengthier articles were cited more often in some journals [23]. In the fields of Infectious Diseases, Clinical Microbiology and Antimicrobial Agents, brief reports were cited less often than full articles, even after adjustment for the journal impact factor [24]. This was not the case in another study assessing 504 articles and adjusting for several confounding factors [13].…”

Section: Discussionmentioning

confidence: 97%

The Impact of Article Length on the Number of Future Citations: A Bibliometric Analysis of General Medicine Journals

et al. 2013

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BackgroundThe number of citations received is considered an index of study quality and impact. We aimed to examine the factors associated with the number of citations of published articles, focusing on the article length.MethodsOriginal human studies published in the first trimester of 2006 in 5 major General Medicine journals were analyzed with regard to the number of authors and of author-affiliated institutions, title and abstract word count, article length (number of print pages), number of bibliographic references, study design, and 2006 journal impact factor (JIF). A multiple linear regression model was employed to identify the variables independently associated with the number of article citations received through January 2012.ResultsOn univariate analysis the JIF, number of authors, article length, study design (interventional/observational and prospective/retrospective), title and abstract word count, number of author-affiliated institutions, and number of references were all associated with the number of citations received. On multivariate analysis with the logarithm of citations as the dependent variable, only article length [regression coefficient: 14.64 (95% confidence intervals: (5.76–23.50)] and JIF [3.37 (1.80–4.948)] independently predicted the number of citations. The variance of citations explained by these parameters was 51.2%.ConclusionIn a sample of articles published in major General Medicine journals, in addition to journal impact factors, article length and number of authors independently predicted the number of citations. This may reflect a higher complexity level and quality of longer and multi-authored studies.

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Section: Discussionmentioning

confidence: 97%

The Impact of Article Length on the Number of Future Citations: A Bibliometric Analysis of General Medicine Journals

et al. 2013

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“…The citation impact of a publication can be influenced by many factors. In the medical sciences, previous studies have for instance analyzed the effect of study design (e.g., case report, randomized controlled trial, or meta-analysis; Patsopoulos, Analatos, & Ioannidis, 2005), article type (i.e., brief report or full-size article; Mavros, Bardakas, Rafailidis, Sardi, Demetriou, & Falagas, 2013), and article length (Falagas, Zarkali, Karageorgopoulos, Bardakas, & Mavros, 2013). In this paper, the effect of differences in citation practices between medical research areas has been investigated.…”

Section: Discussionmentioning

confidence: 99%

Citation Analysis May Severely Underestimate the Impact of Clinical Research as Compared to Basic Research

et al. 2013

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BackgroundCitation analysis has become an important tool for research performance assessment in the medical sciences. However, different areas of medical research may have considerably different citation practices, even within the same medical field. Because of this, it is unclear to what extent citation-based bibliometric indicators allow for valid comparisons between research units active in different areas of medical research.MethodologyA visualization methodology is introduced that reveals differences in citation practices between medical research areas. The methodology extracts terms from the titles and abstracts of a large collection of publications and uses these terms to visualize the structure of a medical field and to indicate how research areas within this field differ from each other in their average citation impact.ResultsVisualizations are provided for 32 medical fields, defined based on journal subject categories in the Web of Science database. The analysis focuses on three fields: Cardiac & cardiovascular systems, Clinical neurology, and Surgery. In each of these fields, there turn out to be large differences in citation practices between research areas. Low-impact research areas tend to focus on clinical intervention research, while high-impact research areas are often more oriented on basic and diagnostic research.ConclusionsPopular bibliometric indicators, such as the h-index and the impact factor, do not correct for differences in citation practices between medical fields. These indicators therefore cannot be used to make accurate between-field comparisons. More sophisticated bibliometric indicators do correct for field differences but still fail to take into account within-field heterogeneity in citation practices. As a consequence, the citation impact of clinical intervention research may be substantially underestimated in comparison with basic and diagnostic research.

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“…There is no consensus about the best regression method for citation data. Methods used so far include ordinary least squares linear regression (Aksnes, Rørstad, Piro, & Sivertsen, 2013;Dragos & Dragos, 2014 [citations per publication used as the dependant variable]; Foo & Tan, 2014;He, 2009;Mavros, Bardakas, Rafailidis et al, 2013;Rigby, 2013 [adding 1 to citations, dividing by a time normalised value and taking their log]; Tang, 2013 [adding 1 to citations and taking their log]; Stewart, 1983), logistic regression (Baldi, 1998;Bornmann, & Williams, 2013;Kutlar, Kabasakal, & Ekici, 2013;Sin, 2011;Willis, Bahler, Neuberger, & Dahm, 2011;Xia & Nakanishi, 2012;Yu, Yu, & Wang, 2014), a distribution-free regression method (Peters & van Raan, 1994), multinomial logistic regression (Baumgartner & Leydesdorff, 2014) and negative binomial regression (Chen, 2012;Didegah & Thelwall, 2013ab;McDonald, 2007;Thelwall & Maflahi, in press [for altmetrics]; Walters, 2006;Yoshikane, 2013 [for patent citations]).…”

Section: Introductionmentioning

confidence: 99%

Regression for citation data: An evaluation of different methods

Thelwall

Wilson

2014

Journal of Informetrics

117

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Citations are increasingly used for research evaluations. It is therefore important to identify factors affecting citation scores that are unrelated to scholarly quality or usefulness so that these can be taken into account. Regression is the most powerful statistical technique to identify these factors and hence it is important to identify the best regression strategy for citation data. Citation counts tend to follow a discrete lognormal distribution and, in the absence of alternatives, have been investigated with negative binomial regression. Using simulated discrete lognormal data (continuous lognormal data rounded to the nearest integer) this article shows that a better strategy is to add one to the citations, take their log and then use the general linear (ordinary least squares) model for regression (e.g., multiple linear regression, ANOVA), or to use the generalised linear model without the log. Reasonable results can also be obtained if all the zero citations are discarded, the log is taken of the remaining citation counts and then the general linear model is used, or if the generalised linear model is used with the continuous lognormal distribution. Similar approaches are recommended for altmetric data, if it proves to be lognormally distributed

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Comparison of number of citations to full original articles versus brief reports

Cited by 7 publications

References 6 publications

The Impact of Article Length on the Number of Future Citations: A Bibliometric Analysis of General Medicine Journals

The Impact of Article Length on the Number of Future Citations: A Bibliometric Analysis of General Medicine Journals

Citation Analysis May Severely Underestimate the Impact of Clinical Research as Compared to Basic Research

Regression for citation data: An evaluation of different methods

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