Journal Guide

Statistical Methods and Applications (SMA) is the official Journal of the Italian Statistical Society. This international journal fosters the development of statistical methodology and its applications in biological, demographic, economic, health, physical, social, and other scientific domains. In particular, the journal emphasizes investigations of methodological foundations and methods that have broad applications. SMA includes two sections. The first is devoted to statistical methodology, publishing original contributions in all fields of statistics. In addition, this section periodically publishes critical reviews and discussions on recent developments in statistical theory and methods. The second section publishes papers devoted to original and innovative applications of recent statistical methodology and complex approaches of statistical data analysis.Officially cited as: Stat Methods Appl

Statistical Methods in Medical Research is a highly ranked, peer reviewed scholarly journal and is the leading vehicle for review articles in all the main areas of medical statistics and therefore an essential reference for all medical statisticians. It is particularly useful for medical researchers dealing with data and provides a key resource for medical and statistical libraries, as well as pharmaceutical companies.This unique journal is devoted solely to statistics and medicine and aims to keep professionals abreast of the many powerful statistical techniques now available to the medical profession. As techniques are constantly adopted by statisticians working both inside and outside the medical environment, this review journal aims to satisfy the increasing demand for accurate and up-to-the-minute information.Why choose Statistical Methods in Medical Research?Covers all areas of medical statisticsFull of statistics and statistical techniquesContains the latest, accurate informationAn indispensable reference for medical statisticians, statistical libraries and pharmaceutical companies.

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.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. The website address is http://stat.uibk.ac.at/SMIJThe 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 Methodology for papers on new statistical modelling ideas. These papers will be based upon a problem of real substantive interest with appropriate data.* 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.It is expected that the author will submit several suggestions for possible reviewers who are in the application area when submitting the manuscript.

Statistical Papers provides a forum for the presentation and critical assessment of statistical methods. In particular, the journal encourages the discussion of methodological foundations as well as potential applications. This journal stresses statistical methods that have broad applications; however, it does give special attention to statistical methods that are relevant to the economic and social sciences. In addition to original research papers, readers will find survey articles, short notes, reports on statistical software, problem section, and book reviews.Officially cited as: Stat Papers

Statistics publishes theoretical and applied papers related to the different fields of statistics such as regression and variance analysis, design of experiments, foundations of statistical inference, statistical decision theory, testing hypotheses, parameter estimation, nonparametric methods, sequential procedures, time series and statistical problems for stochastic processes, and statistical data analysis. It is expected that the papers give interesting and novel contributions to statistical theory and its applications at a good mathematical level. The results should be presented in form of theorems together with their mathematical proofs, which should not be merely routine calculations. Additionally, the discussion of results and their value for the theory or for applications could be a valuable addition, as well as numerical results on the efficiency or examples for the application of the theoretical results. A special section is devoted to survey papers on theory and methods in interesting areas of statistics. The Journal may also publish proceedings of conferences and announcements on related topics. All published research articles in this journal have undergone rigorous peer review, based on initial editor screening and anonymous refereeing by independent expert referees. Disclaimer Taylor & Francis makes every effort to ensure the accuracy of all the information (the 'Content') contained in its publications. However, Taylor & Francis and its agents and licensors make no representations or warranties whatsoever as to the accuracy, completeness or suitability for any purpose of the Content and disclaim all such representations and warranties whether express or implied to the maximum extent permitted by law. Any views expressed in this publication are the views of the authors and are not the views of Taylor & Francis.

Statistics and Computing is a bi-monthly refereed journal that publishes papers covering the interface between the statistical and computing sciences.

The journal includes techniques for evaluating analytically intractable problems, such as bootstrap resampling, Markov chain Monte Carlo, sequential Monte Carlo, approximate Bayesian computation,  search and optimization methods, stochastic simulation and Monte Carlo, graphics, computer environments, statistical approaches to software errors, information retrieval, machine learning, statistics of databases and database technology, huge data sets and big data analytics, computer algebra, graphical models, image processing, tomography, inverse problems and uncertainty quantification.

Aim and Scope: Statistics and Its Interface is an international statistical journal promoting the interface between statistics and other disciplines including, but not limited to, biomedical sciences, geosciences, computer sciences, engineering, and social and behavioral sciences. The journal publishes high-quality articles in broad areas of statistical science, emphasizing substantive problems, sound statistical models and methods, clear and efficient computational algorithms, and insightful discussions of the motivating problems.

Statistics & Probability Letters adopts a novel and highly innovative approach to the publication of research findings in statistics and probability. It features concise articles, rapid publication and broad coverage of the statistics and probability literature.Statistics & Probability Letters is a refereed journal. Articles will be limited to six journal pages (13 double-space typed pages) including references and figures. Apart from the six-page limitation, originality, quality and clarity will be the criteria for choosing the material to be published in Statistics & Probability Letters. Every attempt will be made to provide the first review of a submitted manuscript within three months of submission.The proliferation of literature and long publication delays have made it difficult for researchers and practitioners to keep up with new developments outside of, or even within, their specialization. The aim of Statistics & Probability Letters is to help to alleviate this problem. Concise communications (letters) allow readers to quickly and easily digest large amounts of material and to stay up-to-date with developments in all areas of statistics and probability.The mainstream of Letters will focus on new statistical methods, theoretical results, and innovative applications of statistics and probability to other scientific disciplines. Key results and central ideas must be presented in a clear and concise manner. These results may be part of a larger study that the author will submit at a later time as a full length paper to SPL or to another journal. Theory and methodology may be published with proofs omitted, or only sketched, but only if sufficient support material is provided so that the findings can be verified. Empirical and computational results that are of significant value will be published. We also plan to publish applications and case studies that demonstrate a novel use of existing techniques or have interesting innovative ideas about data collection, modelling or inference.

Statistics in Biopharmaceutical Research accepts papers that discuss appropriate statistical methodology and information regarding the use of statistics in all phases of research, development, and practice in the pharmaceutical, biopharmaceutical, device, and diagnostics industries. Articles should focus on the development of novel statistical methods, novel applications of current methods, or the innovative application of statistical principles that can be used by statistical practitioners in these disciplines. Areas of application may include statistical methods for drug discovery, including papers that address issues of multiplicity, sequential trials, adaptive designs, etc.; preclinical and clinical studies; genomics and proteomics; bioassay; biomarkers and surrogate markers; models and analyses of drug history, including pharmacoeconomics, product life cycle, detection of adverse events in clinical studies, and postmarketing risk assessment; regulatory guidelines, including issues of standardization of terminology (e.g., CDISC), tolerance and specification limits related to pharmaceutical practice, and novel methods of drug approval; and detection of adverse events in clinical and toxicological studies. Tutorial articles also are welcome. Articles should include demonstrable evidence of the usefulness of this methodology (presumably by means of an application).

The Editorial Board of SBR intends to ensure that the journal continually provides important, useful, and timely information. To accomplish this, the board strives to attract outstanding articles by seeing that each submission receives a careful, thorough, and prompt review.

Statistics in Biosciences (SIB) is published twice a year in print and electronic form. It aims at development and application of statistical methods and their interface with other quantitative methods, such as computational and mathematical methods, in biological and life science, health science, and biopharmaceutical and biotechnological science. SIB publishes scientific papers and review articles in four sections, with the first two sections as the primary sections. Original Articles publish novel statistical and quantitative methods in biosciences. The Bioscience Case Studies and Practice Articles publish papers that advance statistical practice in biosciences, such as case studies, innovative applications of existing methods that further understanding of subject-matter science, evaluation of existing methods and data sources. Review Articles publish papers that review an area of statistical and quantitative methodology, software, and data sources in biosciences. Commentaries provide perspectives of research topics or policy issues that are of current quantitative interest in biosciences, reactions to an article published in the journal, and scholarly essays. Substantive science is essential in motivating and demonstrating the methodological development and use for an article to be acceptable. Articles published in SIB share the goal of promoting evidence-based real world practice and policy making through effective and timely interaction and communication of statisticians and quantitative researchers with subject-matter scientists in biosciences.

The journal aims to influence practice in medicine and its associated sciences through the publication of papers on statistical and other quantitative methods. Papers will explain new methods and either demonstrate their application, preferably through a substantive, real, motivating example or a comprehensive evaluation based on an illustrative example. Alternatively, papers will report on case-studies where creative use or technical generalizations of established methodology is directed towards a substantive application. Reviews of, and tutorials on, general topics relevant to the application of statistics to medicine will also be published. The main criteria for publication will be appropriateness of the statistical methods to a particular medical problem and clarity of exposition. Papers with primarily mathematical content will be excluded. The journal aims to enhance communication between statisticians, clinicians and medical researchers.

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2008 Impact Factor: 0.642Ranking: 70/92 in Statistics & Probability2008 5-Year Impact Factor: 0.892 169;2009 Thomson Reuters, 2008 Journal Citation Reports174;Stochastic Models is devoted to the theory and applications of probability as they arise in the modeling of phenomena in the natural sciences and technology. It presents contributions on the mathematical methodology, from structural, analytical, and algorithmic to experimental approaches. It offers an interdisciplinary presentation on the uses of probability theory and discusses practical applications of stochastic models to diverse areas such as biology, computer science/telecommunications modeling, inventories and dams, reliability, storage, queuing theory, and operations research.Publication office: Taylor & Francis, Inc., 325 Chestnut Street, Suite 800, Philadelphia, PA 19106.

Stochastic Processes and their Applications publishes papers on the theory and applications of stochastic processes. It is concerned with concepts and techniques, and is oriented towards a broad spectrum of mathematical, scientific and engineering interests.Characterization, structural properties, inference and control of stochastic processes are covered. The journal is exacting and scholarly in its standards. Every effort is made to promote innovation, vitality, and communication between disciplines. All papers are refereed.Benefits to authorsWe also provide many author benefits, such as free PDFs, a liberal copyright policy, special discounts on Elsevier publications and much more. Please click here for more information on our author services.Please see our Guide for Authors for information on article submission. If you require any further information or help, please visit our support pages: http://support.elsevier.com