About this journal
Aims and scope
The purpose of Sequential Analysis is to contribute to theoretical and applied aspects of sequential methodologies in all areas of statistical science. Published papers highlight the development of new and important sequential approaches.
Interdisciplinary articles that emphasize the methodology of practical value to applied researchers and statistical consultants are highly encouraged. Papers that cover contemporary areas of applications including animal abundance, bioequivalence, communication science, computer simulations, data mining, directional data, disease mapping, environmental sampling, genome, imaging, microarrays, networking, parallel processing, pest management, sonar detection, spatial statistics, tracking, and engineering are deemed especially important. Of particular value are expository review articles that critically synthesize broad-based statistical issues. Papers on case-studies are also considered. All papers are refereed. Publication office: Taylor & Francis, Inc., 530 Walnut Street, Suite 850, Philadelphia, PA 19106.
The journal emphasizes both readability and relevance to all statisticians and does not exclusively cater to a handful of specialists in the field of sequential analysis. Readership includes statisticians, mathematicians, biostatisticians, scientists, probabilists, clinicians, quality control managers, and engineers.
Journal metrics
Usage
- 14K annual downloads/views
Citation metrics
- 0.6 (2023) Impact Factor
- 0.7 (2023) 5 year IF
- 1.4 (2023) CiteScore (Scopus)
- 0.841 (2023) SNIP
- 0.414 (2023) SJR
Speed/acceptance
- 2 days avg. from submission to first decision
- 72 days avg. from submission to first post-review decision
- 62 days avg. from acceptance to online publication
- 30% acceptance rate
Understanding and using journal metrics
Journal metrics can be a useful tool for readers, as well as for authors who are deciding where to submit their next manuscript for publication. However, any one metric only tells a part of the story of a journal’s quality and impact. Each metric has its limitations which means that it should never be considered in isolation, and metrics should be used to support and not replace qualitative review.
We strongly recommend that you always use a number of metrics, alongside other qualitative factors such as a journal’s aims & scope, its readership, and a review of past content published in the journal. In addition, a single article should always be assessed on its own merits and never based on the metrics of the journal it was published in.
For more details, please read the Author Services guide to understanding journal metrics.
Journal metrics in brief
Usage and acceptance rate data above are for the last full calendar year and are updated annually in February. Speed data is updated every six months, based on the prior six months. Citation metrics are updated annually mid-year. Please note that some journals do not display all of the following metrics (find out why).
- Usage: the total number of times articles in the journal were viewed by users of Taylor & Francis Online in the previous calendar year, rounded to the nearest thousand.
Citation Metrics
- Impact Factor*: the average number of citations received by articles published in the journal within a two-year window. Only journals in the Clarivate Science Citation Index Expanded (SCIE), Social Sciences Citation Index (SSCI), Arts and Humanities Citation Index (AHCI) and the Emerging Sources Citation Index (ESCI) have an Impact Factor.
- Impact Factor Best Quartile*: the journal’s highest subject category ranking in the Journal Citation Reports. Q1 = 25% of journals with the highest Impact Factors.
- 5 Year Impact Factor*: the average number of citations received by articles in the journal within a five-year window.
- CiteScore (Scopus)†: the average number of citations received by articles in the journal over a four-year period.
- CiteScore Best Quartile†: the journal’s highest CiteScore ranking in a Scopus subject category. Q1 = 25% of journals with the highest CiteScores.
- SNIP (Source Normalized Impact per Paper): the number of citations per paper in the journal, divided by citation potential in the field.
- SJR (Scimago Journal Rank): Average number of (weighted) citations in one year, divided by the number of articles published in the journal in the previous three years.
Speed/acceptance
- From submission to first decision: the average (median) number of days for a manuscript submitted to the journal to receive a first decision. Based on manuscripts receiving a first decision in the last six months.
- From submission to first post-review decision: the average (median) number of days for a manuscript submitted to the journal to receive a first decision if it is sent out for peer review. Based on manuscripts receiving a post-review first decision in the last six months.
- From acceptance to online publication: the average (median) number of days from acceptance of a manuscript to online publication of the Version of Record. Based on articles published in the last six months.
- Acceptance rate: articles accepted for publication by the journal in the previous calendar year as percentage of all papers receiving a final decision.
For more details on the data above, please read the Author Services guide to understanding journal metrics.
*Copyright: Journal Citation Reports®, Clarivate Analytics
†Copyright: CiteScore™, Scopus
Editorial board
Editor-in-Chief
Nitis Mukhopadhyay
Department of Statistics
CLAS Bldg, Box 4120
University of Connecticut
Storrs, CT 06269-4120, USA
Tel: 860-486-6144
Fax: 860-486-4113
E-mail: [email protected]
Associate Editors
Makoto Aoshima - Institute of Mathematics, University of Tsukuba, Ibaraki, JAPAN
Michael Baron - Department of Mathematics and Statistics, American University, Washington, D.C., U.S.A.
Debanjan Bhattacharjee - Department of Mathematics, Utah Valley University, Orem, UT, U.S.A
Marco Bonetti - Bocconi University, Milan, ITALY
Elena Buzaianu - Department of Mathematics and Statistics, University of North Florida, Jacksonville, U.S.A.
Hock Peng Chan - Department of Statistics & Applied Probability, National University of Singapore, Singapore, REPUBLIC OF SINGAPORE
Yuan-chin Ivan Chang - Institute of Statistical Science Academia Sinica, Taipei, TAIWAN
Bhargab Chattopadhyay - Indian Istitute of Information Technology Vadodara, Gujarat, INDIA
Saibal Chattopadhyay - Operations Management Group, Indian Institute of Management Calcutta, Kolkata, INDIA
Pinyuen Chen - Department of Mathematics, Syracuse University, Syracuse, NY, U.S.A.
Pankaj Choudhary - Department of Mathematical Sciences, University of Texas at Dallas, Richardson, TX, U.S.A.
D. Stephen Coad - School of Mathematical Sciences, University of London, UNITED KINGDOM
Shyamal Krishna De - School of Mathematical Sciences, National Institute of Science Education and Research, INDIA
Joe Glaz - Department of Statistics, University of Connecticut, Storrs, CT, U.S.A.
David Goldsman - School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, GA, U.S.A.
Edit Gombay - Department of Mathematical & Statistical Sciences, University of Alberta, Edmonton, Alberta, CANADA
Marie Huskova - Department of Statistics, Charles University, Prague, CZECH REPUBLIC
Kartlos Kachiashvili - Georgian Technical University and I. Vekua Institute of Applied Mathematics, Tbilisi State University, GEORGIA
Jan Kalina - Institute of Computer Science of the Czech Academy of Sciences, CZECH REPUBLIC
Sangyeol Lee - Department of Statistics, Seoul National University, Seoul, KOREA
Yajun Mei - H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, U.S.A.
Amitava Mukherjee - XLRI- Xavier School of Management, Jamshedpur, INDIA
Ivair Ramos Silva - Department of Statistics, Federal University of Ouro Preto MG, BRAZIL
William F. Rosenberger - School of Information Technology and Engineering, George Mason University, Fairfax, VA, U.S.A.
Wolfgang Schmid - Department of Statistics, European University, Frankfurt (Oder), GERMANY
T. K. S. Solanky - Department of Mathematics, University of New Orleans, New Orleans, LA, U.S.A.
T. N. Sriram - Department of Statistics, University of Georgia, Athens, GA, U.S.A.
Ansgar Steland - Institute of Statistics, RWTH Aachen University, Aachen, GERMANY
Alexander Tartakovsky - Department of Statistics, University of Connecticut, Storrs, CT, U.S.A.
H.K. Tony Ng - Department of Statistical Science, Southern Methodist University, Dallas, TX, U.S.A.
Yaser Samadi - Department of Mathematics, Southern Illinois University, Carbondale, IL, U.S.A
Tae Yang - Department of Mathematics, Myongji University, Yongin, KOREA
Kazuyoshi Yata - Institute of Mathematics, University of Tsukuba, Ibaraki, JAPAN
Yao Xie- H. Milton Stewart School of Industrial and Systems Engineering, Georgia Institute of Technology, Atlanta, Georgia, U.S.A .
Shelley Zacks - Department of Mathematical Sciences, Binghamton University, Binghamton, NY, U.S.A.
Gideon K.D. Zamba - Department of Biostatistics, University of Iowa, Iowa City, IA, U.S.A.
Abstracting and indexing
Sequential Analysis is Abstracted and Indexed in the following:
CSA Technology Research Database
Current Index to Statistics
Genamics JournalSeek
MathSciNet
Mathematical Reviews
Scopus
Statistical Theory and Method Abstracts
zbMATH
Open access
Sequential Analysis is a hybrid open access journal that is part of our Open Select publishing program, giving you the option to publish open access. Publishing open access means that your article will be free to access online immediately on publication, increasing the visibility, readership, and impact of your research.
Why choose open access?
- Increase the discoverability and readership of your article
- Make an impact and reach new readers, not just those with easy access to a research library
- Freely share your work with anyone, anywhere
- Comply with funding mandates and meet the requirements of your institution, employer or funder
- Rigorous peer review for every open access article
Article Publishing Charges (APC)
If you choose to publish open access in this journal you may be asked to pay an Article Publishing Charge (APC). You may be able to publish your article at no cost to yourself or with a reduced APC if your institution or research funder has an open access agreement or membership with Taylor & Francis.
Use our APC finder to calculate your article publishing charge
4 issues per year
Currently known as:
- Sequential Analysis: Design Methods and Applications (1984 - current)
Formerly known as
- Communications in Statistics. Part C: Sequential Analysis (1982 - 1983)
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