IDEAS home Printed from https://ideas.repec.org/a/spr/scient/v116y2018i2d10.1007_s11192-018-2801-z.html
   My bibliography  Save this article

A mixed longitudinal and cross-sectional model to forecast the journal impact factor in the field of Dentistry

Author

Listed:
  • Pilar Valderrama

    (University of Granada)

  • Manuel Escabias

    (University of Granada)

  • Evaristo Jiménez-Contreras

    (University of Granada)

  • Mariano J. Valderrama

    (University of Granada)

  • Pilar Baca

    (University of Granada)

Abstract

In order to estimate the impact factor value for a journal in Dentistry, two sets of variables were considered in this study: the first takes in the longitudinal behavior of the process specified in the slope and intercept of the straight line fitted to the trend of the last years, whereas the second considers the percentage of review papers published each year and the adhesion degree of the journal to ICMJE guidelines. The final estimated model showed a high determination coefficient (99.3%) and its performance was tested on a new set of journals randomly sampled from the list of journal citation reports.

Suggested Citation

  • Pilar Valderrama & Manuel Escabias & Evaristo Jiménez-Contreras & Mariano J. Valderrama & Pilar Baca, 2018. "A mixed longitudinal and cross-sectional model to forecast the journal impact factor in the field of Dentistry," Scientometrics, Springer;Akadémiai Kiadó, vol. 116(2), pages 1203-1212, August.
    • Handle: RePEc:spr:scient:v:116:y:2018:i:2:d:10.1007_s11192-018-2801-z
    DOI: 10.1007/s11192-018-2801-z
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s11192-018-2801-z
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s11192-018-2801-z?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
    ---><---

    As the access to this document is restricted, you may want to

    for a different version of it.

    References listed on IDEAS

    as
    1. Pilar Valderrama & Manuel Escabias & Evaristo Jiménez-Contreras & Alberto Rodríguez-Archilla & Mariano J. Valderrama, 2018. "Proposal of a stochastic model to determine the bibliometric variables influencing the quality of a journal: application to the field of Dentistry," Scientometrics, Springer;Akadémiai Kiadó, vol. 115(2), pages 1087-1095, May.
    2. Sungmin Park, 2015. "The R&D logic model: Does it really work? An empirical verification using successive binary logistic regression models," Scientometrics, Springer;Akadémiai Kiadó, vol. 105(3), pages 1399-1439, December.
    3. Wah Yun Low & Kwan Hoong Ng & M. A. Kabir & Ai Peng Koh & Janaki Sinnasamy, 2014. "Erratum to: Trend and impact of international collaboration in clinical medicine papers published in Malaysia," Scientometrics, Springer;Akadémiai Kiadó, vol. 100(2), pages 607-607, August.
    4. Tian Yu & Guang Yu & Peng-Yu Li & Liang Wang, 2014. "Citation impact prediction for scientific papers using stepwise regression analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 101(2), pages 1233-1252, November.
    5. Liping Yu & Houqiang Yu, 2016. "Does the average JIF percentile make a difference?," Scientometrics, Springer;Akadémiai Kiadó, vol. 109(3), pages 1979-1987, December.
    6. Yifan Qian & Wenge Rong & Nan Jiang & Jie Tang & Zhang Xiong, 2017. "Citation regression analysis of computer science publications in different ranking categories and subfields," Scientometrics, Springer;Akadémiai Kiadó, vol. 110(3), pages 1351-1374, March.
    7. Xingchen Li & Qiang Wu & Yuanyuan Liu, 2017. "A quantitative analysis of researcher citation personal display considering disciplinary differences and influence factors," Scientometrics, Springer;Akadémiai Kiadó, vol. 113(2), pages 1093-1112, November.
    8. Claudia Contreras & Gonzalo Edwards & Alejandra Mizala, 2006. "The Current Impact Factor and the long-term impact of scientific journals by discipline: A logistic diffusion model estimation," Scientometrics, Springer;Akadémiai Kiadó, vol. 69(3), pages 689-696, December.
    9. Samreen Ayaz & Nayyer Masood & Muhammad Arshad Islam, 2018. "Predicting scientific impact based on h-index," Scientometrics, Springer;Akadémiai Kiadó, vol. 114(3), pages 993-1010, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Pilar Valderrama & Evaristo Jiménez-Contreras & Manuel Escabias & Mariano J. Valderrama, 2022. "Introducing a bibliometric index based on factor analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 509-522, January.
    2. Wanjun Xia & Tianrui Li & Chongshou Li, 2023. "A review of scientific impact prediction: tasks, features and methods," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 543-585, January.

    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. Pilar Valderrama & Evaristo Jiménez-Contreras & Manuel Escabias & Mariano J. Valderrama, 2022. "Introducing a bibliometric index based on factor analysis," Scientometrics, Springer;Akadémiai Kiadó, vol. 127(1), pages 509-522, January.
    2. Wan Siti Nur Aiza & Liyana Shuib & Norisma Idris & Nur Baiti Afini Normadhi, 2024. "Features, techniques and evaluation in predicting articles’ citations: a review from years 2010–2023," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(1), pages 1-29, January.
    3. Wanjun Xia & Tianrui Li & Chongshou Li, 2023. "A review of scientific impact prediction: tasks, features and methods," Scientometrics, Springer;Akadémiai Kiadó, vol. 128(1), pages 543-585, January.
    4. Kayvan Kousha & Mike Thelwall, 2024. "Factors associating with or predicting more cited or higher quality journal articles: An Annual Review of Information Science and Technology (ARIST) paper," Journal of the Association for Information Science & Technology, Association for Information Science & Technology, vol. 75(3), pages 215-244, March.
    5. Juan Xie & Kaile Gong & Jiang Li & Qing Ke & Hyonchol Kang & Ying Cheng, 2019. "A probe into 66 factors which are possibly associated with the number of citations an article received," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1429-1454, June.
    6. Nunkoo, Robin & Hall, C. Michael & Rughoobur-Seetah, Soujata & Teeroovengadum, Viraiyan, 2019. "Citation practices in tourism research: Toward a gender conscientious engagement," Annals of Tourism Research, Elsevier, vol. 79(C).
    7. Deming Lin & Tianhui Gong & Wenbin Liu & Martin Meyer, 2020. "An entropy-based measure for the evolution of h index research," Scientometrics, Springer;Akadémiai Kiadó, vol. 125(3), pages 2283-2298, December.
    8. Ajiferuke, Isola & Famoye, Felix, 2015. "Modelling count response variables in informetric studies: Comparison among count, linear, and lognormal regression models," Journal of Informetrics, Elsevier, vol. 9(3), pages 499-513.
    9. He, Guoxiu & Lin, Chenxi & Ren, Jiayu & Duan, Peichen, 2024. "Predicting the emergence of disruptive technologies by comparing with references via soft prompt-aware shared BERT," Journal of Informetrics, Elsevier, vol. 18(4).
    10. Wang, Yuzhuo & Xiang, Yi & Zhang, Chengzhi, 2024. "Exploring motivations for algorithm mention in the domain of natural language processing: A deep learning approach," Journal of Informetrics, Elsevier, vol. 18(4).
    11. Salim Sazzed, 2021. "Association between the Rankings of Top Bioinformatics and Medical Informatics Journals and the Scholarly Reputations of Chief Editors," Publications, MDPI, vol. 9(3), pages 1-15, September.
    12. Ivone de Bem Oliveira & Rhewter Nunes & Lucia Mattiello & Stela Barros-Ribeiro & Isabela Pavanelli Souza & Alexandre Siqueira Guedes Coelho & Rosane Garcia Collevatti, 2019. "Research and partnership in studies of sugarcane using molecular markers: a scientometric approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(1), pages 335-355, April.
    13. Mingyang Wang & Zhenyu Wang & Guangsheng Chen, 2019. "Which can better predict the future success of articles? Bibliometric indices or alternative metrics," Scientometrics, Springer;Akadémiai Kiadó, vol. 119(3), pages 1575-1595, June.
    14. Jakub Rybacki & Dobromił Serwa, 2021. "What Makes a Successful Scientist in a Central Bank? Evidence From the RePEc Database," Central European Journal of Economic Modelling and Econometrics, Central European Journal of Economic Modelling and Econometrics, vol. 13(3), pages 331-357, September.
    15. Balázs Győrffy & Andrea Magda Nagy & Péter Herman & Ádám Török, 2018. "Factors influencing the scientific performance of Momentum grant holders: an evaluation of the first 117 research groups," Scientometrics, Springer;Akadémiai Kiadó, vol. 117(1), pages 409-426, October.
    16. Michael Färber & Lazaros Tampakis, 2024. "Analyzing the impact of companies on AI research based on publications," Scientometrics, Springer;Akadémiai Kiadó, vol. 129(1), pages 31-63, January.
    17. Wang, Jiang-Pan & Guo, Qiang & Zhou, Lei & Liu, Jian-Guo, 2019. "Dynamic credit allocation for researchers," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 208-216.
    18. Hui Xuan Tan & Ephrance Abu Ujum & Kwai Fatt Choong & Kuru Ratnavelu, 2015. "Impact analysis of domestic and international research collaborations: a Malaysian case study," Scientometrics, Springer;Akadémiai Kiadó, vol. 102(1), pages 885-904, January.
    19. Bornmann, Lutz & Leydesdorff, Loet, 2015. "Does quality and content matter for citedness? A comparison with para-textual factors and over time," Journal of Informetrics, Elsevier, vol. 9(3), pages 419-429.
    20. Bai, Xiaomei & Zhang, Fuli & Lee, Ivan, 2019. "Predicting the citations of scholarly paper," Journal of Informetrics, Elsevier, vol. 13(1), pages 407-418.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    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:spr:scient:v:116:y:2018:i:2:d:10.1007_s11192-018-2801-z. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.