Statistical Modelling
Journal Title
- Statistical Modelling
ISSN
- E 1477-0342 | P 1471-082X | 1471-082X | 1477-0342
Publisher
- SAGE Publications
- SAGE
Listed on(Coverage)
| JCR | 2005-2019 |
|---|---|
| SJR | 2002-2019 |
| CiteScore | 2011-2019 |
| SCIE | 2010-2021 |
| SCOPUS | 2017-2020 |
Active
- Active
based on the information
- SCOPUS:2020-10
Country
- ENGLAND
Aime & Scopes
- 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.