IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0201590.html
   My bibliography  Save this article

Dissemination of novel biostatistics methods: Impact of programming code availability and other characteristics on article citations

Author

Listed:
  • Amy E Wahlquist
  • Lutfiyya N Muhammad
  • Teri Lynn Herbert
  • Viswanathan Ramakrishnan
  • Paul J Nietert

Abstract

Background: As statisticians develop new methodological approaches, there are many factors that influence whether others will utilize their work. This paper is a bibliometric study that identifies and quantifies associations between characteristics of new biostatistics methods and their citation counts. Of primary interest was the association between numbers of citations and whether software code was available to the reader. Methods: Statistics journal articles published in 2010 from 35 statistical journals were reviewed by two biostatisticians. Generalized linear mixed models were used to determine which characteristics (author, article, and journal) were independently associated with citation counts (as of April 1, 2017) in other peer-reviewed articles. Results: Of 722 articles reviewed, 428 were classified as new biostatistics methods. In a multivariable model, for articles that were not freely accessible on the journal’s website, having code available appeared to offer no boost to the number of citations (adjusted rate ratio = 0.96, 95% CI = 0.74 to 1.24, p = 0.74); however, for articles that were freely accessible on the journal’s website, having code available was associated with a 2-fold increase in the number of citations (adjusted rate ratio = 2.01, 95% CI = 1.30 to 3.10, p = 0.002). Higher citation rates were also associated with higher numbers of references, longer articles, SCImago Journal Rank indicator (SJR), and total numbers of publications among authors, with the strongest impact on citation rates coming from SJR (rate ratio = 1.21 for a 1-unit increase in SJR; 95% CI = 1.11 to 1.32). Conclusion: These analyses shed new insight into factors associated with citation rates of articles on new biostatistical methods. Making computer code available to readers is a goal worth striving for that may enhance biostatistics knowledge translation.

Suggested Citation

  • Amy E Wahlquist & Lutfiyya N Muhammad & Teri Lynn Herbert & Viswanathan Ramakrishnan & Paul J Nietert, 2018. "Dissemination of novel biostatistics methods: Impact of programming code availability and other characteristics on article citations," PLOS ONE, Public Library of Science, vol. 13(8), pages 1-12, August.
    • Handle: RePEc:plo:pone00:0201590
    DOI: 10.1371/journal.pone.0201590
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0201590
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0201590&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0201590?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Haiqun Lin & Daniel O. Scharfstein & Robert A. Rosenheck, 2004. "Analysis of longitudinal data with irregular, outcome‐dependent follow‐up," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 66(3), pages 791-813, August.
    2. Réjean Landry & Nabil Amara & Mathieu Ouimet, 2007. "Determinants of knowledge transfer: evidence from Canadian university researchers in natural sciences and engineering," The Journal of Technology Transfer, Springer, vol. 32(6), pages 561-592, December.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Roberto Iorio & Sandrine Labory & Francesco Rentocchini, 2014. "Academics’ Motivations and Depth and Breadth of Knowledge Transfer Activities," Working Papers 1401, c.MET-05 - Centro Interuniversitario di Economia Applicata alle Politiche per L'industria, lo Sviluppo locale e l'Internazionalizzazione.
    2. Na Cai & Wenbin Lu & Hao Helen Zhang, 2012. "Time-Varying Latent Effect Model for Longitudinal Data with Informative Observation Times," Biometrics, The International Biometric Society, vol. 68(4), pages 1093-1102, December.
    3. Fang Li & Sheng Zhang & Yuhuan Jin, 2018. "Sustainability of University Technology Transfer: Mediating Effect of Inventor’s Technology Service," Sustainability, MDPI, vol. 10(6), pages 1-17, June.
    4. David Grosse Kathoefer & Jens Leker, 2012. "Knowledge transfer in academia: an exploratory study on the Not-Invented-Here Syndrome," The Journal of Technology Transfer, Springer, vol. 37(5), pages 658-675, October.
    5. Attila Varga & Márton Horváth, 2014. "Institutional and regional factors behind university patenting in Europe: an exploratory spatial analysis using EUMIDA data," Chapters, in: Andrea Bonaccorsi (ed.), Knowledge, Diversity and Performance in European Higher Education, chapter 6, pages iii-iii, Edward Elgar Publishing.
    6. Crespi, Gustavo & D'Este, Pablo & Fontana, Roberto & Geuna, Aldo, 2011. "The impact of academic patenting on university research and its transfer," Research Policy, Elsevier, vol. 40(1), pages 55-68, February.
    7. Novotny, Ádám, 2013. "Az egyetemi-ipari technológiatranszfer sajátosságai Magyarországon [The features of university-industry technology transfer in Hungary]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(10), pages 1119-1139.
    8. de Jong, Stefan P.L. & Wardenaar, Tjerk & Horlings, Edwin, 2016. "Exploring the promises of transdisciplinary research: A quantitative study of two climate research programmes," Research Policy, Elsevier, vol. 45(7), pages 1397-1409.
    9. Berna Beyhan & M. Teoman Pamukçu & Erkan Erdil, 2011. "Individual and Organizational Aspects of University-Industry Relations in Nanotechnology: The Turkish Case," STPS Working Papers 1106, STPS - Science and Technology Policy Studies Center, Middle East Technical University, revised Jun 2011.
    10. Sylvaine Castellano & Philippe Davidson & Insaf Khelladi, 2017. "Creativity techniques to enhance knowledge transfer within global virtual teams in the context of knowledge-intensive enterprises," The Journal of Technology Transfer, Springer, vol. 42(2), pages 253-266, April.
    11. Ana Fernández & Esther Ferrándiz & M. Dolores León, 2021. "Are organizational and economic proximity driving factors of scientific collaboration? Evidence from Spanish universities, 2001–2010," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(1), pages 579-602, January.
    12. Erikson, Truls & Knockaert, Mirjam & Foo, Maw Der, 2015. "Enterprising scientists: The shaping role of norms, experience and scientific productivity," Technological Forecasting and Social Change, Elsevier, vol. 99(C), pages 211-221.
    13. Nabil Amara & Réjean Landry, 2012. "Counting citations in the field of business and management: why use Google Scholar rather than the Web of Science," Scientometrics, Springer;Akadémiai Kiadó, vol. 93(3), pages 553-581, December.
    14. Maietta, Ornella Wanda, 2015. "Determinants of R&D University-Frim Collaboration and Its Impact on Innovation: a Perspective from the Italian Food and Drink Industry," 2015 Conference, August 9-14, 2015, Milan, Italy 225668, International Association of Agricultural Economists.
    15. Norrin Halilem & Nabil Amara & Réjean Landry, 2011. "Is the academic Ivory Tower becoming a managed structure? A nested analysis of the variance in activities of researchers from natural sciences and engineering in Canada," Scientometrics, Springer;Akadémiai Kiadó, vol. 86(2), pages 431-448, February.
    16. Cristian Barra & Ornella Wanda Maietta & Roberto Zotti, 2017. "First, Second and Third Tier Universities: Academic Excellence, Local Knowledge Spillovers and Innovation in Europe," CSEF Working Papers 468, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
    17. Oscar Llopis & Mabel Sánchez-Barrioluengo & Julia Olmos-Peñuela & Elena Castro-Martínez, 2018. "Scientists’ engagement in knowledge transfer and exchange: Individual factors, variety of mechanisms and users," Science and Public Policy, Oxford University Press, vol. 45(6), pages 790-803.
    18. Maietta, Ornella Wanda, 2015. "Determinants of university–firm R&D collaboration and its impact on innovation: A perspective from a low-tech industry," Research Policy, Elsevier, vol. 44(7), pages 1341-1359.
    19. Peter McCullagh, 2008. "Sampling bias and logistic models," Journal of the Royal Statistical Society Series B, Royal Statistical Society, vol. 70(4), pages 643-677, September.
    20. Maria Tsouri, 2022. "Knowledge networks and strong tie creation: the role of relative network position," Journal of Geographical Systems, Springer, vol. 24(1), pages 95-114, January.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0201590. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.