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# Journal of Statistical Software 4 Year Journal Impact IF - Analysis · Trend · Prediction · Ranking

15.952

-43.4 %

## Journal of Statistical Software

##### Journal Impact IF Ranking
Subcategory Quartile Rank Percentile
Statistics and Probability Q1 1/239

### Statistics and Probability 99%

Statistics, Probability and Uncertainty Q1 1/152

### Statistics, Probability and Uncertainty 99%

Software Q1 10/389

### Software 97%

Journal Impact IF Ranking

## Journal of Statistical Software

The 2021-2022 4 Year Journal Impact IF of Journal of Statistical Software is 15.952, which is just updated in 2022.

## Journal of Statistical Software

##### Journal Key Metrics
Journal Title Journal of Statistical Software 1548-7660 - University of California at Los Angeles - 1996 - Present YES English https://academic-accelerator.com//Publication-Fee/Journal-of-Statistical-Software https://www.jstatsoft.org/index https://www.jstatsoft.org/pages/view/authors http://en.wikipedia.org/wiki/Journal_of_Statistical_Software

## Journal of Statistical Software

##### Impact Factor 2022-2023 Prediction

Journal of Statistical Software Impact Factor Prediction System is now online. You can start share your valuable insights with the community.

## What is Impact Factor?

The impact factor (IF) or journal impact factor (JIF) of an academic journal is a scientometric index calculated by Clarivate that reflects the yearly average number of citations of articles published in the last two years in a given journal. It is frequently used as a proxy for the relative importance of a journal within its field; journals with higher impact factor values are often deemed to be more important, or carry more intrinsic prestige in their respective fields, than those with lower values.

Impact factor is commonly used to evaluate the relative importance of a journal within its field and to measure the frequency with which the “average article” in a journal has been cited in a particular time period. Journal which publishes more review articles will get highest IFs. Journals with higher IFs believed to be more important than those with lower ones. According to Eugene Garfield “impact simply reflects the ability of the journals and editors to attract the best paper available.” Journal which publishes more review articles will get maximum IFs. The Impact Factor of an academic journal is a scientometric Metric that reflects the yearly average number of citations that recent articles published in a given journal received. It is frequently used as a Metric for the relative importance of a journal within its field; journals with higher Impact Factor are often deemed to be more important than those with lower ones. The Journal of Statistical Software Impact Factor IF measures the average number of citations received in a particular year (2021) by papers published in the Journal of Statistical Software during the two preceding years (2019-2020). Note that 2021 Impact Factor are reported in 2022; they cannot be calculated until all of the 2021 publications have been processed by the indexing agency. New journals, which are indexed from their first published issue, will receive an impact factor after two years of indexing; in this case, the citations to the year prior to Volume 1, and the number of articles published in the year prior to Volume 1, are known zero values. Journals that are indexed starting with a volume other than the first volume will not get an impact factor until they have been indexed for three years. Occasionally, Journal Citation Reports assigns an impact factor to new journals with less than two years of indexing, based on partial citation data. The calculation always uses two complete and known years of item counts, but for new titles one of the known counts is zero. Annuals and other irregular publications sometimes publish no items in a particular year, affecting the count. The impact factor relates to a specific time period; it is possible to calculate it for any desired period. In addition to the 2-year Impact Factor, the 3-year Impact Factor, 4-year Impact Factor, 5-year Impact Factor, Real-Time Impact Factor can provide further insights and factors into the impact of Journal of Statistical Software.

## History

The impact factor was devised by Eugene Garfield, the founder of the Institute for Scientific Information (ISI). Impact factors are calculated yearly starting from 1975 for journals listed in the Journal Citation Reports (JCR). ISI was acquired by Thomson Scientific & Healthcare in 1992, and became known as Thomson ISI. In 2018, Thomson ISI was sold to Onex Corporation and Baring Private Equity Asia. They founded a new corporation, Clarivate, which is now the publisher of the JCR.

## Use

The impact factor is used to compare different journals within a certain field. The Web of Science indexes more than 11,500 science and social science journals. Journal impact factors are often used to evaluate the merit of individual articles and individual researchers. This use of impact factors was summarised by Hoeffel:

Impact Factor is not a perfect tool to measure the quality of articles but there is nothing better and it has the advantage of already being in existence and is, therefore, a good technique for scientific evaluation. Experience has shown that in each specialty the best journals are those in which it is most difficult to have an article accepted, and these are the journals that have a high impact factor. Most of these journals existed long before the impact factor was devised. The use of impact factor as a measure of quality is widespread because it fits well with the opinion we have in each field of the best journals in our specialty....In conclusion, prestigious journals publish papers of high level. Therefore, their impact factor is high, and not the contrary.

Eugene Garfield

In brief, Impact factors may be used by:
• Authors to decide where to submit an article for publication.
• Libraries to make collection development decisions
• Academic departments to make decisions on promotion and tenure.
As impact factors are a journal-level metric, rather than an article- or individual-level metric, this use is controversial. Garfield agrees with Hoeffel,but warns about the "misuse in evaluating individuals" because there is "a wide variation [of citations] from article to article within a single journal". Other things to consider about Impact Factors:
• Many journals do not have an impact factor.
• The impact factor cannot assess the quality of individual articles. Even if citations were evenly distributed among articles, the impact factor would only measure the interests of other researchers in an article, not its importance and usefulness.
• Only research articles, technical notes and reviews are “citable” items. Editorials, letters, news items and meeting abstracts are “non-citable items”.
• Only a small percentage of articles are highly cited and they are found in a small subset of journals. This small proportion accounts for a large percentage of citations.
• Controversial papers, such as those based on fraudulent data, may be highly cited, distorting the impact factor of a journal.
• Citation bias may exist. For example, English language resources may be favoured. Authors may cite their own work.
Moreover, informed and careful use of these impact data is essential, and should be based on a thorough understanding of the methodology used to generate impact factors. There are controversial aspects of using impact factors:
• It is not clear whether the number of times a paper is cited measures its actual quality.
• Some databases that calculate impact factors fail to incorporate publications including textbooks, handbooks and reference books.
• Certain disciplines have low numbers of journals and usage. Therefore, one should only compare journals or researchers within the same discipline.
• Review articles normally are cited more often and therefore can skew results.
• Self-citing may also skew results.
• Some resources used to calculate impact factors have inadequate international coverage.
• Editorial policies can artificially inflate an impact factor.
Impact factors have often been used in advancement and tenure decision-making. Many recognize that this is a coarse tool for such important decisions, and that a multitude of factors should be taken into account in these deliberations. When considering the use of the impact factor (IF), keep these aspects in mind:
• IF analysis is limited to citations from the journals indexed by the Web of Science/Web of Knowledge. Currently, the Web of Science indexes only 8621 journals across the full breadth of the sciences, and just 3121 in the social sciences.
• A high IF/citation rate says nothing about the quality -- or even, validity -- of the references being cited. Notorious or even retracted articles often attract a lot of attention, hence a high number of citations. The notority related to the first publication on "cold fusion" is one such example.
• Journals that publish more "review articles" are often found near the top of the rankings. While not known for publishing new, creative findings, these individual articles tend to be heavily cited.
• The IF measures the average number of citations to articles in the journal -- given this, a small number of highly-cited articles will skew the figure.
• It takes several years for new journals to be added to the list of titles indexed by the Web of Science/Web of Knowledge, so these newer titles will be under-represented.
• It's alleged that journal editors have learned to "game" the system, encouraging authors to cite their works previously published in the same journal.
Comparing Journals Across Disciplines? Not a good idea! Using Impact Factors within a given discipline should only be done with great care, as described above. Using impact factor data to compare journals across disciplines is even more problematic. Here are some of the reasons:
• Disciplines where older literature is still referenced, such as Chemistry and Mathematics, offer challenges to the methodolgy since older citations (older than two years) are not used to calculate the impact factor for a given journal. (Five-year impact factor analysis, which can be calculated using the Journal Citation Index database, helps smooth out this problem only to some degree.)
• Different disciplines have different practices regarding tendency to cite larger numbers of references. Higher overall citation rates will bump upward impact factor measurements.
• Where it's common for large numbers of authors to collaborate on a single paper, such as in Physics, the tendency of authors to cite themselves (and in this case, more authors) will result in increased citation rates.

## Pros and Cons of the Impact Factor

Pros:

• A vetted, established metric for measuring journal impact within a discipline.
• Designed to eliminate bias based on journal size and frequency.
Cons:
• Individual articles makes an uneven contribution to overall Impact Factor.
• Impact Factor does not account for certain things, things like context (postive or negative citaion) and intentionality (self-citation).
• The metric is proprietary to and bound by the contents of the Thomson Reuters database.
• Citations, on which the Impact Factor is based, count for less than 1% of an article's overall use.

## Criticism

Numerous critiques have been made regarding the use of impact factors. A 2007 study noted that the most fundamental flaw is that impact factors present the mean of data that are not normally distributed, and suggested that it would be more appropriate to present the median of these data. There is also a more general debate on the validity of the impact factor as a measure of journal importance and the effect of policies that editors may adopt to boost their impact factor (perhaps to the detriment of readers and writers). Other criticism focuses on the effect of the impact factor on behavior of scholars, editors and other stakeholders. Others have made more general criticisms, arguing that emphasis on impact factor results from negative influence of neoliberal policies on academia claiming that what is needed is not just replacement of the impact factor with more sophisticated metrics for science publications but also discussion on the social value of research assessment and the growing precariousness of scientific careers in higher education.
Experts stress that there are limitations in using impact factors to evaluate a scholar's work. There are many reasons cited for not relying on impact factor alone to evaluate the output of a particular individual. Among these are the following:

• A single factor is not sufficient for evaluating an author's work.
• Journal values are meaningless unless compared within the same discipline. Impact factors vary among disciplines.
• The impact factor was originally devised to show the impact of a specific journal, not a specific scholar. The quality and impact of the author's work may extend beyond the impact of a particular journal.
According to Jim Testa, a researcher for ThomsonReuters Scientific, the most widespread misuse of the Impact Factor is to evaluate the work of an individual author (instead of a journal). "To say that because a researcher is publishing in a certain journal, he or she is more influential or deserves more credit is not necessarily true. There are many other variables to consider." (interview 6/26/2008 in Thomson Reuters blog entry)

Journal of Statistical Software
Journal Profile

The Journal of Statistical Software (JSS) publishes open-source software and corresponding reproducible articles discussing all aspects of the design, implementation, documentation, application, evaluation, comparison, maintainance and distribution of software dedicated to improvement of state-of-the-art in statistical computing in all areas of empirical research. Open-source code and articles are jointly reviewed and published in this journal and should be accessible to a broad community of practitioners, teachers, and researchers in the field of statistics. The Journal of Statistical Software is a peer-reviewed open-access scientific journal that publishes papers related to statistical software. The Journal of Statistical Software was founded in 1996 by Jan de Leeuw of the Department of Statistics at the University of California, Los Angeles. Its current editors-in-chief are Achim Zeileis, Bettina GrÃ¼n, Edzer Pebesma, and Torsten Hothorn. It is published by the Foundation for Open Access Statistics. The journal charges no author fees or subscription fees.

ISSN
1548-7660
ISSN

ISSN (Online)
-
ISSN (Online)

### The ISSN (Online) of Journal of Statistical Software is - . An ISSN is an 8-digit code used to identify newspapers, journals, magazines and periodicals of all kinds and on all media–print and electronic. Journal of Statistical Software Key Factor Analysis

Publisher
University of California at Los Angeles
Publisher

### Journal of Statistical Software is published by University of California at Los Angeles . Journal of Statistical Software Key Factor Analysis

Publication Frequency
-
Publication Frequency

Coverage
1996 - Present
Coverage

Open Access
YES
Open Access

Publication Fee
Publication Fee

Language
English
Language

Country/Region
United States
Country/Region

## Journal of Statistical Software

Total Publications
1389
Total Citations
246676

## Journal of Statistical Software

Year Publications Citations
Year Publications Citations
1996 3 0
1997 10 2
1998 2 7
1999 9 4
2000 9 32
2001 7 45
2002 13 74
2003 21 201
2004 39 321
2005 45 494
2006 38 693
2007 83 956
2008 64 1421
2009 72 2105
2010 87 3405
2011 105 5087
2012 93 7222
2013 61 9725
2014 90 13154
2015 105 16274
2016 102 21061
2017 107 27957
2018 88 32313
2019 56 41950
2020 76 57412
2021 4 4761
Publications Cites Dataset