A quick and easy method to estimate the random effect on citation measures

Nieuwenhuysen, Paul; Rousseau, Ronald

doi:10.1007/bf02095762

Cited by 14 publications

(7 citation statements)

References 7 publications

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“…Such uncertainty measures can be found in Schubert and Glänzel (1983), Nieuwenhuysen and Rousseau (1988), Opthof (1997), Chen, Jen, andWu (2014), Greenwood (2007), and Stern (2013). The latter two articles show that, besides the very top journals, a distinct discrimination in terms of the level of the impact factor between closely spaced journals is not possible.…”

mentioning

confidence: 99%

How robust are journal rankings based on the impact factor? Evidence from the economic sciences

Seiler

Wohlrabe

2014

Journal of Informetrics

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Standard-Nutzungsbedingungen:Die Dokumente auf EconStor dürfen zu eigenen wissenschaftlichen Zwecken und zum Privatgebrauch gespeichert und kopiert werden.Sie dürfen die Dokumente nicht für öffentliche oder kommerzielle Zwecke vervielfältigen, öffentlich ausstellen, öffentlich zugänglich machen, vertreiben oder anderweitig nutzen.Sofern die Verfasser die Dokumente unter Open-Content-Lizenzen (insbesondere CC-Lizenzen) zur Verfügung gestellt haben sollten, gelten abweichend von diesen Nutzungsbedingungen die in der dort genannten Lizenz gewährten Nutzungsrechte. It is well-known that the distribution of citations to articles in a journal is skewed. We ask whether journal rankings based on the impact factor are robust with respect to this fact. We exclude the most cited paper, the top 5 and 10 cited papers for 100 economics journals and recalculate the impact factor. Afterwards we compare the resulting rankings with the original ones from 2012. Our results show that the rankings are relatively robust. This holds both for the 2-year and the 5-year impact factor. Terms of use: Documents in EconStor mayJEL-Code: A120, A140.

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mentioning

confidence: 99%

How robust are journal rankings based on the impact factor? Evidence from the economic sciences

Seiler

Wohlrabe

2014

Journal of Informetrics

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“…Before presenting our formal development, it must be said that models based on correlation indices or statistical parameters-standard deviation, variance, or other dispersion measures-have been considered in previous works-for example the ones presented in [38,39]. It must be mentioned here that in general these kinds of indices are not always considered to be useful, mainly for two reasons.…”

Section: Methodsmentioning

confidence: 99%

Measuring Time-Dynamics and Time-Stability of Journal Rankings in Mathematics and Physics by Means of Fractional p-Variations

2017

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Journal rankings of specific research fields are often used for evaluation purposes, both of authors and institutions. These rankings can be defined by means of several methods, as expert assessment, scholarly-based agreements, or by the ordering induced by a numeric index associated to the prestige of the journals. In order to be efficient and accepted by the research community, it must preserve the ordering over time, at least up to a point. Otherwise, the procedure for defining the ranking must be revised to assure that it reflects the presumably stable characteristic "prestige" that it claims to be quantifying. A mathematical model based on fractional p-variations of the values of the order number of each journal in a time series of journal rankings is explained, and its main properties are shown. As an example, we study the evolution of two given ordered lists of journals through an eleven-year series. These journal ranks are defined by using the 2-year Impact Factor of Thomson-Reuters (nowadays Clarivate Analytics) lists for MATHEMATICS and PHYSICS, APPLIED from 2002 to 2013. As an application of our model, we define an index that precludes the use of journal ranks for evaluation purposes when some minimal requirements on the associated fractional p-variations are not satisfied. The final conclusion is that the list of mathematics does not satisfy the requirements on the p-variations, while the list of applied physics does.

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“…A further question is whether different sets give different rankings, even for those journals that are included in the intersection of two lists, say an experimental one and ISI'S list. A caveat is in order here, since a shift in rank can often be explained by pure random fluctuations [13,14].…”

Section: Ideas For a Practical Experimentsmentioning

confidence: 98%

Do a Field List of Internationally Visible Journals and Their Journal Impact Factors Depend on the Initial Set of Journals? A Research Proposal

Rousseau¹,

Spinak²

1996

Journal of Documentation

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A quick and easy method to estimate the random effect on citation measures

Cited by 14 publications

References 7 publications

How robust are journal rankings based on the impact factor? Evidence from the economic sciences

How robust are journal rankings based on the impact factor? Evidence from the economic sciences

Measuring Time-Dynamics and Time-Stability of Journal Rankings in Mathematics and Physics by Means of Fractional p-Variations

Do a Field List of Internationally Visible Journals and Their Journal Impact Factors Depend on the Initial Set of Journals? A Research Proposal

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