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Leydesdorff, L.; Bornmann, L.; Mutz, R.; Opthof, T.: Turning the tables on citation analysis one more time : principles for comparing sets of documents (2011)
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- Abstract
- We submit newly developed citation impact indicators based not on arithmetic averages of citations but on percentile ranks. Citation distributions are-as a rule-highly skewed and should not be arithmetically averaged. With percentile ranks, the citation score of each paper is rated in terms of its percentile in the citation distribution. The percentile ranks approach allows for the formulation of a more abstract indicator scheme that can be used to organize and/or schematize different impact indicators according to three degrees of freedom: the selection of the reference sets, the evaluation criteria, and the choice of whether or not to define the publication sets as independent. Bibliometric data of seven principal investigators (PIs) of the Academic Medical Center of the University of Amsterdam are used as an exemplary dataset. We demonstrate that the proposed family indicators [R(6), R(100), R(6, k), R(100, k)] are an improvement on averages-based indicators because one can account for the shape of the distributions of citations over papers.
- Source
- Journal of the American Society for Information Science and Technology. 62(2011) no.7, S.1370-1381
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Bornmann, L.; Mutz, R.: From P100 to P100' : a new citation-rank approach (2014)
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- Abstract
- Properties of a percentile-based rating scale needed in bibliometrics are formulated. Based on these properties, P100 was recently introduced as a new citation-rank approach (Bornmann, Leydesdorff, & Wang, 2013). In this paper, we conceptualize P100 and propose an improvement which we call P100'. Advantages and disadvantages of citation-rank indicators are noted.
- Date
- 22. 8.2014 17:05:18
- Source
- Journal of the Association for Information Science and Technology. 65(2014) no.9, S.1939-1943
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Bornmann, L.; Mutz, R.; Daniel, H.D.: Do we need the h index and its variants in addition to standard bibliometric measures? (2009)
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- Abstract
- In this study, we investigate whether there is a need for the h index and its variants in addition to standard bibliometric measures (SBMs). Results from our recent study (L. Bornmann, R. Mutz, & H.-D. Daniel, 2008) have indicated that there are two types of indices: One type of indices (e.g., h index) describes the most productive core of a scientist's output and informs about the number of papers in the core. The other type of indices (e.g., a index) depicts the impact of the papers in the core. In evaluative bibliometric studies, the two dimensions quantity and quality of output are usually assessed using the SBMs number of publications (for the quantity dimension) and total citation counts (for the impact dimension). We additionally included the SBMs into the factor analysis. The results of the newly calculated analysis indicate that there is a high intercorrelation between number of publications and the indices that load substantially on the factor Quantity of the Productive Core as well as between total citation counts and the indices that load substantially on the factor Impact of the Productive Core. The high-loading indices and SBMs within one performance dimension could be called redundant in empirical application, as high intercorrelations between different indicators are a sign for measuring something similar (or the same). Based on our findings, we propose the use of any pair of indicators (one relating to the number of papers in a researcher's productive core and one relating to the impact of these core papers) as a meaningful approach for comparing scientists.
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- h-Index
- Source
- Journal of the American Society for Information Science and Technology. 60(2009) no.6, S.1286-1289
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-
Mutz, R.; Bornmann, L.; Daniel, H.-D.: Testing for the fairness and predictive validity of research funding decisions : a multilevel multiple imputation for missing data approach using ex-ante and ex-post peer evaluation data from the Austrian science fund (2015)
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- Abstract
- It is essential for research funding organizations to ensure both the validity and fairness of the grant approval procedure. The ex-ante peer evaluation (EXANTE) of N?=?8,496 grant applications submitted to the Austrian Science Fund from 1999 to 2009 was statistically analyzed. For 1,689 funded research projects an ex-post peer evaluation (EXPOST) was also available; for the rest of the grant applications a multilevel missing data imputation approach was used to consider verification bias for the first time in peer-review research. Without imputation, the predictive validity of EXANTE was low (r?=?.26) but underestimated due to verification bias, and with imputation it was r?=?.49. That is, the decision-making procedure is capable of selecting the best research proposals for funding. In the EXANTE there were several potential biases (e.g., gender). With respect to the EXPOST there was only one real bias (discipline-specific and year-specific differential prediction). The novelty of this contribution is, first, the combining of theoretical concepts of validity and fairness with a missing data imputation approach to correct for verification bias and, second, multilevel modeling to test peer review-based funding decisions for both validity and fairness in terms of potential and real biases.
- Source
- Journal of the Association for Information Science and Technology. 66(2015) no.11, S.2321-2339
- Type
- a
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Leydesdorff, L.; Bornmann, L.; Wagner, C.S.: ¬The relative influences of government funding and international collaboration on citation impact (2019)
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- Abstract
- A recent publication in Nature reports that public R&D funding is only weakly correlated with the citation impact of a nation's articles as measured by the field-weighted citation index (FWCI; defined by Scopus). On the basis of the supplementary data, we up-scaled the design using Web of Science data for the decade 2003-2013 and OECD funding data for the corresponding decade assuming a 2-year delay (2001-2011). Using negative binomial regression analysis, we found very small coefficients, but the effects of international collaboration are positive and statistically significant, whereas the effects of government funding are negative, an order of magnitude smaller, and statistically nonsignificant (in two of three analyses). In other words, international collaboration improves the impact of research articles, whereas more government funding tends to have a small adverse effect when comparing OECD countries.
- Date
- 8. 1.2019 18:22:45
- Source
- Journal of the Association for Information Science and Technology. 70(2019) no.2, S.198-201
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Bornmann, L.; Bauer, J.; Haunschild, R.: Distribution of women and men among highly cited scientists (2015)
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- Journal of the Association for Information Science and Technology. 66(2015) no.12, S.2715-2716
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Bornmann, L.; Mutz, R.; Daniel, H.-D.: Are there better indices for evaluation purposes than the h index? : a comparison of nine different variants of the h index using data from biomedicine (2008)
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- Abstract
- In this study, we examined empirical results on the h index and its most important variants in order to determine whether the variants developed are associated with an incremental contribution for evaluation purposes. The results of a factor analysis using bibliographic data on postdoctoral researchers in biomedicine indicate that regarding the h index and its variants, we are dealing with two types of indices that load on one factor each. One type describes the most productive core of a scientist's output and gives the number of papers in that core. The other type of indices describes the impact of the papers in the core. Because an index for evaluative purposes is a useful yardstick for comparison among scientists if the index corresponds strongly with peer assessments, we calculated a logistic regression analysis with the two factors resulting from the factor analysis as independent variables and peer assessment of the postdoctoral researchers as the dependent variable. The results of the regression analysis show that peer assessments can be predicted better using the factor impact of the productive core than using the factor quantity of the productive core.
- Source
- Journal of the American Society for Information Science and Technology. 59(2008) no.5, S.830-837
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Bornmann, L.; Mutz, R.; Daniel, H.-D.: Multilevel-statistical reformulation of citation-based university rankings : the Leiden ranking 2011/2012 (2013)
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- Abstract
- Since the 1990s, with the heightened competition and the strong growth of the international higher education market, an increasing number of rankings have been created that measure the scientific performance of an institution based on data. The Leiden Ranking 2011/2012 (LR) was published early in 2012. Starting from Goldstein and Spiegelhalter's (1996) recommendations for conducting quantitative comparisons among institutions, in this study we undertook a reformulation of the LR by means of multilevel regression models. First, with our models we replicated the ranking results; second, the reanalysis of the LR data showed that only 5% of the PPtop10% total variation is attributable to differences between universities. Beyond that, about 80% of the variation between universities can be explained by differences among countries. If covariates are included in the model the differences among most of the universities become meaningless. Our findings have implications for conducting university rankings in general and for the LR in particular. For example, with Goldstein-adjusted confidence intervals, it is possible to interpret the significance of differences among universities meaningfully: Rank differences among universities should be interpreted as meaningful only if their confidence intervals do not overlap.
- Source
- Journal of the American Society for Information Science and Technology. 64(2013) no.8, S.1649-1658
- Type
- a
-
Marx, W.; Bornmann, L.: On the problems of dealing with bibliometric data (2014)
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- Date
- 18. 3.2014 19:13:22
- Source
- Journal of the Association for Information Science and Technology. 65(2014) no.4, S.866-867
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- a
-
Bornmann, L.: How well does a university perform in comparison with its peers? : The use of odds, and odds ratios, for the comparison of institutional citation impact using the Leiden Rankings (2015)
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- Abstract
- This study presents the calculation of odds, and odds ratios, for the comparison of the citation impact of universities in the Leiden Ranking. Odds and odds ratios can be used to measure the performance difference between a selected university and competing institutions, or the average of selected competitors, in a relatively simple but clear way.
- Editor
- Mutz, R.
- Source
- Journal of the Association for Information Science and Technology. 66(2015) no.12, S.2711-2713
- Type
- a
-
Bornmann, L.; Haunschild, R.: Relative Citation Ratio (RCR) : an empirical attempt to study a new field-normalized bibliometric indicator (2017)
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- Abstract
- Hutchins, Yuan, Anderson, and Santangelo (2015) proposed the Relative Citation Ratio (RCR) as a new field-normalized impact indicator. This study investigates the RCR by correlating it on the level of single publications with established field-normalized indicators and assessments of the publications by peers. We find that the RCR correlates highly with established field-normalized indicators, but the correlation between RCR and peer assessments is only low to medium.
- Source
- Journal of the Association for Information Science and Technology. 68(2017) no.4, S.1064-1067
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- a
-
Bornmann, L.; Daniel, H.-D.: What do we know about the h index? (2007)
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- Abstract
- Jorge Hirsch recently proposed the h index to quantify the research output of individual scientists. The new index has attracted a lot of attention in the scientific community. The claim that the h index in a single number provides a good representation of the scientific lifetime achievement of a scientist as well as the (supposed) simple calculation of the h index using common literature databases lead to the danger of improper use of the index. We describe the advantages and disadvantages of the h index and summarize the studies on the convergent validity of this index. We also introduce corrections and complements as well as single-number alternatives to the h index.
- Object
- H-Index
- Source
- Journal of the American Society for Information Science and Technology. 58(2007) no.9, S.1381-1385
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- a
-
Bornmann, L.; Moya Anegón, F. de; Mutz, R.: Do universities or research institutions with a specific subject profile have an advantage or a disadvantage in institutional rankings? (2013)
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- Abstract
- Using data compiled for the SCImago Institutions Ranking, we look at whether the subject area type an institution (university or research-focused institution) belongs to (in terms of the fields researched) has an influence on its ranking position. We used latent class analysis to categorize institutions based on their publications in certain subject areas. Even though this categorization does not relate directly to scientific performance, our results show that it exercises an important influence on the outcome of a performance measurement: Certain subject area types of institutions have an advantage in the ranking positions when compared with others. This advantage manifests itself not only when performance is measured with an indicator that is not field-normalized but also for indicators that are field-normalized.
- Source
- Journal of the American Society for Information Science and Technology. 64(2013) no.11, S.2310-2316
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- a
-
Bornmann, L.; Haunschild, R.: Overlay maps based on Mendeley data : the use of altmetrics for readership networks (2016)
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- Abstract
- Visualization of scientific results using networks has become popular in scientometric research. We provide base maps for Mendeley reader count data using the publication year 2012 from the Web of Science data. Example networks are shown and explained. The reader can use our base maps to visualize other results with the VOSViewer. The proposed overlay maps are able to show the impact of publications in terms of readership data. The advantage of using our base maps is that it is not necessary for the user to produce a network based on all data (e.g., from 1 year), but can collect the Mendeley data for a single institution (or journals, topics) and can match them with our already produced information. Generation of such large-scale networks is still a demanding task despite the available computer power and digital data availability. Therefore, it is very useful to have base maps and create the network with the overlay technique.
- Source
- Journal of the Association for Information Science and Technology. 67(2016) no.12, S.3064-3072
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- a
-
Collins, H.; Bornmann, L.: On scientific misconduct (2014)
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- Source
- Journal of the Association for Information Science and Technology. 65(2014) no.5, S.1089-1090
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- a
-
Bornmann, L.; Mutz, R.: Growth rates of modern science : a bibliometric analysis based on the number of publications and cited references (2015)
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- Abstract
- Many studies (in information science) have looked at the growth of science. In this study, we reexamine the question of the growth of science. To do this we (a) use current data up to publication year 2012 and (b) analyze the data across all disciplines and also separately for the natural sciences and for the medical and health sciences. Furthermore, the data were analyzed with an advanced statistical technique-segmented regression analysis-which can identify specific segments with similar growth rates in the history of science. The study is based on two different sets of bibliometric data: (a) the number of publications held as source items in the Web of Science (WoS, Thomson Reuters) per publication year and (b) the number of cited references in the publications of the source items per cited reference year. We looked at the rate at which science has grown since the mid-1600s. In our analysis of cited references we identified three essential growth phases in the development of science, which each led to growth rates tripling in comparison with the previous phase: from less than 1% up to the middle of the 18th century, to 2 to 3% up to the period between the two world wars, and 8 to 9% to 2010.
- Source
- Journal of the Association for Information Science and Technology. 66(2015) no.11, S.2215-2222
- Type
- a
-
Bornmann, L.; Haunschild, R.: ¬An empirical look at the nature index (2017)
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- Abstract
- In November 2014, the Nature Index (NI) was introduced (see http://www.natureindex.com) by the Nature Publishing Group (NPG). The NI comprises the primary research articles published in the past 12 months in a selection of reputable journals. Starting from two short comments on the NI (Haunschild & Bornmann, 2015a, 2015b), we undertake an empirical analysis of the NI using comprehensive country data. We investigate whether the huge efforts of computing the NI are justified and whether the size-dependent NI indicators should be complemented by size-independent variants. The analysis uses data from the Max Planck Digital Library in-house database (which is based on Web of Science data) and from the NPG. In the first step of the analysis, we correlate the NI with other metrics that are simpler to generate than the NI. The resulting large correlation coefficients point out that the NI produces similar results as simpler solutions. In the second step of the analysis, relative and size-independent variants of the NI are generated that should be additionally presented by the NPG. The size-dependent NI indicators favor large countries (or institutions) and the top-performing small countries (or institutions) do not come into the picture.
- Source
- Journal of the Association for Information Science and Technology. 68(2017) no.3, S.653-659
- Type
- a
-
Bornmann, L.: How to analyze percentile citation impact data meaningfully in bibliometrics : the statistical analysis of distributions, percentile rank classes, and top-cited papers (2013)
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- Date
- 22. 3.2013 19:44:17
- Source
- Journal of the American Society for Information Science and Technology. 64(2013) no.3, S.587-595
- Type
- a
-
Leydesdorff, L.; Bornmann, L.: How fractional counting of citations affects the impact factor : normalization in terms of differences in citation potentials among fields of science (2011)
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- Abstract
- The Impact Factors (IFs) of the Institute for Scientific Information suffer from a number of drawbacks, among them the statistics-Why should one use the mean and not the median?-and the incomparability among fields of science because of systematic differences in citation behavior among fields. Can these drawbacks be counteracted by fractionally counting citation weights instead of using whole numbers in the numerators? (a) Fractional citation counts are normalized in terms of the citing sources and thus would take into account differences in citation behavior among fields of science. (b) Differences in the resulting distributions can be tested statistically for their significance at different levels of aggregation. (c) Fractional counting can be generalized to any document set including journals or groups of journals, and thus the significance of differences among both small and large sets can be tested. A list of fractionally counted IFs for 2008 is available online at http:www.leydesdorff.net/weighted_if/weighted_if.xls The between-group variance among the 13 fields of science identified in the U.S. Science and Engineering Indicators is no longer statistically significant after this normalization. Although citation behavior differs largely between disciplines, the reflection of these differences in fractionally counted citation distributions can not be used as a reliable instrument for the classification.
- Date
- 22. 1.2011 12:51:07
- Source
- Journal of the American Society for Information Science and Technology. 62(2011) no.2, S.217-229
- Type
- a
-
Bornmann, L.; Daniel, H.-D.: Universality of citation distributions : a validation of Radicchi et al.'s relative indicator cf = c/c0 at the micro level using data from chemistry (2009)
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- Abstract
- In a recently published PNAS paper, Radicchi, Fortunato, and Castellano (2008) propose the relative indicator cf as an unbiased indicator for citation performance across disciplines (fields, subject areas). To calculate cf, the citation rate for a single paper is divided by the average number of citations for all papers in the discipline in which the single paper has been categorized. cf values are said to lead to a universality of discipline-specific citation distributions. Using a comprehensive dataset of an evaluation study on Angewandte Chemie International Edition (AC-IE), we tested the advantage of using this indicator in practical application at the micro level, as compared with (1) simple citation rates, and (2) z-scores, which have been used in psychological testing for many years for normalization of test scores. To calculate z-scores, the mean number of citations of the papers within a discipline is subtracted from the citation rate of a single paper, and the difference is then divided by the citations' standard deviation for a discipline. Our results indicate that z-scores are better suited than cf values to produce universality of discipline-specific citation distributions.
- Source
- Journal of the American Society for Information Science and Technology. 60(2009) no.8, S.1664-1670
- Type
- a
