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Statistical Modelling
基本信息
期刊名称 Statistical Modelling
STAT MODEL
期刊ISSN 1471-082X
期刊官方网站 https://journals.sagepub.com/home/SMJ
是否OA No
出版商 SAGE Publications Ltd
出版周期 Quarterly
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始发年份 2001
年文章数 21
最新影响因子 1.2(2023)  scijournal影响因子  greensci影响因子
中科院SCI期刊分区
大类学科 小类学科 Top 综述
数学3区 STATISTICS & PROBABILITY 统计学与概率论3区
CiteScore
CiteScore排名 CiteScore SJR SNIP
学科 排名 百分位 2.2 0.426 0.827
Mathematics
Statistics and Probability
126/278 54%
Decision Sciences
Statistics, Probability and Uncertainty
79/168 53%
补充信息
自引率 8.3%
H-index 35
SCI收录状况 Science Citation Index Expanded
官方审稿时间 登录后查看
网友分享审稿时间 数据统计中,敬请期待。
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PubMed Central (PMC) http://www.ncbi.nlm.nih.gov/nlmcatalog?term=1471-082X%5BISSN%5D
投稿指南
期刊投稿网址 https://us.sagepub.com/en-us/nam/statistical-modelling/journal201837#submission-guidelines
收稿范围
The primary aim of the journal is to publish original and high-quality articles that recognize statistical modelling as the general framework for the application of statistical ideas. Submissions must reflect important developments, extensions, and applications in statistical modelling. The journal also encourages submissions that describe scientifically interesting, complex or novel statistical modelling aspects from a wide diversity of disciplines, and submissions that embrace the diversity of applied statistical modelling. Readers are also encouraged to visit www.statmod.org/journal.htm to download electronic supplements of published papers, which among other items, often provide code and data for reproducibility of analyses.

An important objective and exciting feature of the journal is that the reader should be able to reproduce the results presented in published articles, apply the published techniques to their own problems, and even develop their own extensions of the methodology. To achieve this authors are strongly encouraged to make data and software available over the internet through a website linked to the journal: http://www.statmod.org/smij/

The journal aims to be the major resource for statistical modelling, covering both methodology and practice. Its goal is to be multidisciplinary in nature, promoting the cross-fertilization of ideas between substantive research areas, as well as providing a common forum for the comparison, unification and nurturing of modelling issues across different subjects.

The journal will have three main themes:

New Modelling Concepts and Approaches for papers on new statistical modelling ideas. These papers will be based upon a problem of real substantive interest with appropriate data. Papers that merely propose and study the properties of new methodology based on a standard or well-known model are not appropriate for publication in the journal.

Practical Applications for papers on interesting practical problems which are addressed using an existing or a novel adaptation of an existing modelling technique.

Tutorials & Reviews with papers on recent and cutting edge topics in statistical modelling.

Since "Practical Applications" manuscripts are less common in statistics journals than the other two types, it is worth being more specific concerning the types of manuscripts that fall into this category. Manuscripts should describe statistical analyses of a subject area, where the proposed analyses have rarely (if ever) been done in the application field. This is not, however, sufficient for acceptance for publication. Manuscripts should also provide a thorough literature review of how data of this type are currently handled in the literature of the application area, a review of any applications of modern statistical methodology applied to data of its type in the area, and justification as to why the work is important to the subject area, and provides gains beyond current methodology applied to the field. The methodology used should be modern and reasonably sophisticated (although not necessarily innovative) and should have few or no applications so far in the subject area literature.

The intention in publishing such manuscripts is to provide an opportunity for readers (including those from the application area) to see the potential to revolutionize data analysis in the field. It is also hoped that such publication would provide an outlet for statisticians who may get little recognition in the statistics field for excellent, non-routine, clever, state-of-the-art work in subject areas.

Statistical Modelling wishes to particularly encourage Ph.D. students to submit their original work. As the Editorial Board is aware of the importance of timely publication for articles that are part of a cumulative Ph.D. thesis, we encourage corresponding authors to highlight when the first author is a Ph.D. student. The Editorial Board will then give these articles priority in order to reach a timely decision and will try to provide a fast peer review process in a supportive environment.
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投稿指南 https://journals.sagepub.com/author-instructions/SMJ
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