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Equine Veterinary Journal ISSN 0425-1644 DOI: 10.1111/evj.12400
Editorials
Statistical guidelines for Equine Veterinary Journal ‘Equine Veterinary Journal (EVJ) publishes and promotes high quality peer-reviewed research that expands the knowledge base about equids, informs veterinary science and improves clinical practice.’ EVJ mission statement The EVJ mission statement demands that research published in this journal is of sufficient quality to increase knowledge and enhance clinical practice; in short, we should be able to rely on the conclusions made, but with the caveat that we understand the context and contingencies within which they should be interpreted. Statistics is a branch of science most often dealing with the collection and analysis of numerical data taken from a sample of a population for the purpose of making inference about a larger population. Statistics is an integral part of much biomedical research, and a thorough knowledge of statistical thinking and methods is necessary for the conduct and interpretation of such research. Although it is often included within veterinary curricula (both undergraduate and postgraduate), it is fair to say that the subject is not always popular among students. Likewise, many practising veterinary surgeons and academic veterinary scientists remain unfamiliar with much statistical terminology and practice. Hence, while in an ideal world the readers of the EVJ would be able to evaluate critically all methods (including statistical methods) employed in a study, this is unlikely ever to be the case. Therefore, it is the duty of EVJ’s authors, with the assistance of the editorial team and reviewers, to ensure that methods are used appropriately and that sufficient information is provided to enable careful evaluation by people familiar with the methods. This, then, is the EVJ’s goal for the ‘statistical guidelines’ (Supplementary Item 1) and the ‘statistical checklist’ (Supplementary Item 2), which are being launched in conjunction with this volume and are also available with our Author Guidelines at http://onlinelibrary.wiley.com/journal/10 .1001/%28ISSN%292042-3306. The guidelines set out good practice for the use of statistics in the design, analysis and presentation of studies, highlighting the key point that the role of statistics is not limited to analysis, but rather that statistical thinking is required throughout the research process. The checklist is available to authors, reviewers and readers to help ensure all necessary information is presented in the paper in a clear manner. Good statistical practice aims to facilitate collection of appropriate data (so that the sample is representative of the whole) and enable these data to be summarised in such a way as to enable appropriate conclusions to be drawn regarding the questions of interest. This process may or may not involve formal statistical (hypothesis) testing; when it does, this may
involve relatively simple statistical tests or more ‘complicated’ statistical models. The objective should always be to use the methods that are applicable to the task at hand. There is rarely a single correct approach to statistical analysis of a data-set, although there may be many incorrect approaches. The choice of method depends, to varying degrees, on the question(s) being asked of the data and the purpose for which the conclusions will be applied. Deeper philosophical issues also underpin some choices, such as beliefs about the benefits of Bayesian vs. frequentist frameworks. In the main, these latter considerations are for statistical journals and are not of particular concern to EVJ. However, EVJ is concerned to ensure that statistical methods used in published research are used correctly and transparently, and the recommendations set out in the guidelines seek to help authors to achieve these objectives. It is worth emphasising that the guidelines provide recommendations, not rules. Authors are free to deviate from the guidelines, but should clearly justify their decisions (as they should even when following the guidelines). Authors should also refer to other published guidance relevant to their study, such as that listed in Table 1. Many journals provide statistical guidelines; EVJ has, for a long time, provided some guidance within the ‘Author Guidelines’. The newly released ‘Statistical Guidelines’ (Supplementary Item 1) complement and build upon these. For simplicity, the statistical guidelines are divided into ‘Methods’, ‘Results’ and ‘Discussion’ sections. Within the ‘Methods’ section, the guidelines state that the aims of the study and the study design used to address these aims should be clearly stated; it is only with this information that statistical methods can be evaluated. In fact, authors should carefully consider whether or not statistical analysis is needed or warranted at all. The Methods section of a paper should also have a statistical methods subsection (which may or may not have a heading to this effect). This subsection should ‘describe statistical methods with enough detail to enable a knowledgeable reader with access to the original data to verify the reported results’ [1]. This is, in reality, often difficult to achieve in full, but is a vital component of a well-written paper. With word limits (4000 words in EVJ) it might be thought ‘wasteful’ to use valuable space with seemingly mundane information on statistical methods. Whilst it is likely that at least some explanation of statistical methods should appear within the paper, more detail can be provided in an online supplementary item if necessary. In addition to describing what statistical methods were used (and why), authors should identify which method is used where; a list of statistical tests is insufficient if the reader cannot work out, for each statistical result, which test was used. Of equal importance, authors should explain the steps they have
TABLE 1: Selected reporting guidelines Type of study
Selected guidance
Statistical analysis and reporting Studies involving experimental animals Observational epidemiological studies Randomised trials
• • • • • • • • • • • • •
Diagnostic accuracy Genetic prediction studies Economic evaluations Systematic reviews and meta-analyses Qualitative research
SAMPL ARRIVE STROBE CONSORT SPIRIT REFLECT STARD GRIPS CHEERS PRISMA MOOSE COREQ ENTREQ
http://www.equator-network.org/wp-content/uploads/2013/07/SAMPL-Guidelines-6-27-13.pdf http://www.nc3rs.org.uk/arrive-guidelines http://www.strobe-statement.org http://www.consort-statement.org http://www.spirit-statement.org http://www.reflect-statement.org/statement/ http://www.stard-statement.org Janssens et al. (2011) [2] Husereau et al. (2013) [3] http://www.prisma-statement.org Stroup et al. (2000) [4] http://intqhc.oxfordjournals.org/content/19/6/349.long http://www.biomedcentral.com/1471-2288/12/181
Many of these guidelines can be found on the EQUATOR Network website (http://www.equator-network.org). Equine Veterinary Journal 47 (2015) 131–132 © 2015 EVJ Ltd
131
Statistical guidelines
R. Christley
used to meet the assumptions underlying the statistical method and how they tested the impact of deviations from these assumptions. The guidelines provide relatively straightforward suggestions to ensure that a study’s results are presented in a clear and concise manner. The Results section should include sufficient description of the data to enable readers to understand how the authors arrived at their conclusions. This usually entails provision of estimates of effect (or difference) and measures of variation (usually the 95% confidence interval); other values may also be helpful to readers. P values may be used, but these are less informative than confidence limits, so should only be viewed as additional, rather than alternative, information. It is important that all results can be clearly linked to the methods used in their generation. As well as providing results pertinent to the question(s) at hand, this section should also provide evidence that the assumptions underlying the statistical methods have been considered and the extent to which they are met. Consideration of the limitations of a study, including the statistical analysis, should be paramount in the authors’ minds when they are writing the Discussion section and should be evident to the reader. Common flaws in statistical analyses include the following: explicit or implicit interpretation of a ‘nonsignificant’ P value to mean there is no difference between the groups; conflation of statistical significance with biological or clinical importance; failure to recognise the effect of chance, particularly when multiple statistical testing has been performed; assuming that association is the same as causation; and overinterpretation of the results, such as by inappropriate extrapolation beyond the study or by exaggerating the impact of the findings. Overall, the guidelines seek to encourage good practice and a degree of modesty in the analysis and reporting of research in EVJ. The guidelines are an important step in continued efforts to improve the quality of papers published in EVJ. As noted above, the guidelines are recommendations, not rules, and should not stifle the creativity of EVJ’s authors. They remain
a work in progress and will be updated from time to time. It is hoped that they are a useful addition for both authors and readers, even if they remain largely unnoticed (particularly by the readers of EVJ). R. Christley Statistical Editor, EVJ, Institute of Infection and Global Health, University of Liverpool, UK
References 1. International Committee of Medical Journal Editors (1997) Uniform requirements for manuscripts submitted to biomedical journals. J. Am. Med. Ass. 277, 927-934. 2. Janssens, A.C.J., Ioannidis, J.P., Duijn, C.M., Little, J. and Khoury, M.J. (2011) Strengthening the reporting of genetic risk prediction studies: the GRIPS statement. Br. Med. J. 342, d631. 3. Husereau, D., Drummond, M., Petrou, S., Carswell, C., Moher, D., Greenberg, D., Augustovski, F., Briggs, A.H., Mauskopf, J. and Loder, E. (2013) Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement. BMJ 346, f1049. http://www.ncbi.nlm.nih.gov/pubmed/23529982. Accessed November 10, 2014. 4. Stroup, D.F., Berlin, J.A., Morton, S.C., Olkin, I., Williamson, G.D., Rennie, D., Moher, D., Becker, B.J., Sipe, T.A. and Thacker, S.B. (2000) Meta-analysis of observational studies. J. Am. Med. Ass. 283, 2008-2012.
Supporting Information Additional Supporting Information may be found in the online version of this article at the publisher’s website: Supplementary Item 1: EVJ’s statistical guidelines. Supplementary Item 2: EVJ’s statistical checklist.
Equine Equin ne Veterinary eterinary eter Journal odc d Podcasts EVJs EV VJJs new Podcasts Podcast are now available to download Perfect in-car listening! Download nload ffrom iTunes iTunes https://itunes.ap https://itunes.apple.com/gb/podcast/equine-veterinary-journal/id916700720 pple.com/gb/podcast/e
or wileyonlinelibrary.com/journal/evj wileyonlinelibrary.com/journal/evj
132
Equine Veterinary Journal 47 (2015) 131–132 © 2015 EVJ Ltd
Equine Veterinary Journal ISSN 0425-1644 DOI: 10.1111/evj.12400
Editorials
Statistical guidelines for Equine Veterinary Journal ‘Equine Veterinary Journal (EVJ) publishes and promotes high quality peer-reviewed research that expands the knowledge base about equids, informs veterinary science and improves clinical practice.’ EVJ mission statement The EVJ mission statement demands that research published in this journal is of sufficient quality to increase knowledge and enhance clinical practice; in short, we should be able to rely on the conclusions made, but with the caveat that we understand the context and contingencies within which they should be interpreted. Statistics is a branch of science most often dealing with the collection and analysis of numerical data taken from a sample of a population for the purpose of making inference about a larger population. Statistics is an integral part of much biomedical research, and a thorough knowledge of statistical thinking and methods is necessary for the conduct and interpretation of such research. Although it is often included within veterinary curricula (both undergraduate and postgraduate), it is fair to say that the subject is not always popular among students. Likewise, many practising veterinary surgeons and academic veterinary scientists remain unfamiliar with much statistical terminology and practice. Hence, while in an ideal world the readers of the EVJ would be able to evaluate critically all methods (including statistical methods) employed in a study, this is unlikely ever to be the case. Therefore, it is the duty of EVJ’s authors, with the assistance of the editorial team and reviewers, to ensure that methods are used appropriately and that sufficient information is provided to enable careful evaluation by people familiar with the methods. This, then, is the EVJ’s goal for the ‘statistical guidelines’ (Supplementary Item 1) and the ‘statistical checklist’ (Supplementary Item 2), which are being launched in conjunction with this volume and are also available with our Author Guidelines at http://onlinelibrary.wiley.com/journal/10 .1001/%28ISSN%292042-3306. The guidelines set out good practice for the use of statistics in the design, analysis and presentation of studies, highlighting the key point that the role of statistics is not limited to analysis, but rather that statistical thinking is required throughout the research process. The checklist is available to authors, reviewers and readers to help ensure all necessary information is presented in the paper in a clear manner. Good statistical practice aims to facilitate collection of appropriate data (so that the sample is representative of the whole) and enable these data to be summarised in such a way as to enable appropriate conclusions to be drawn regarding the questions of interest. This process may or may not involve formal statistical (hypothesis) testing; when it does, this may
involve relatively simple statistical tests or more ‘complicated’ statistical models. The objective should always be to use the methods that are applicable to the task at hand. There is rarely a single correct approach to statistical analysis of a data-set, although there may be many incorrect approaches. The choice of method depends, to varying degrees, on the question(s) being asked of the data and the purpose for which the conclusions will be applied. Deeper philosophical issues also underpin some choices, such as beliefs about the benefits of Bayesian vs. frequentist frameworks. In the main, these latter considerations are for statistical journals and are not of particular concern to EVJ. However, EVJ is concerned to ensure that statistical methods used in published research are used correctly and transparently, and the recommendations set out in the guidelines seek to help authors to achieve these objectives. It is worth emphasising that the guidelines provide recommendations, not rules. Authors are free to deviate from the guidelines, but should clearly justify their decisions (as they should even when following the guidelines). Authors should also refer to other published guidance relevant to their study, such as that listed in Table 1. Many journals provide statistical guidelines; EVJ has, for a long time, provided some guidance within the ‘Author Guidelines’. The newly released ‘Statistical Guidelines’ (Supplementary Item 1) complement and build upon these. For simplicity, the statistical guidelines are divided into ‘Methods’, ‘Results’ and ‘Discussion’ sections. Within the ‘Methods’ section, the guidelines state that the aims of the study and the study design used to address these aims should be clearly stated; it is only with this information that statistical methods can be evaluated. In fact, authors should carefully consider whether or not statistical analysis is needed or warranted at all. The Methods section of a paper should also have a statistical methods subsection (which may or may not have a heading to this effect). This subsection should ‘describe statistical methods with enough detail to enable a knowledgeable reader with access to the original data to verify the reported results’ [1]. This is, in reality, often difficult to achieve in full, but is a vital component of a well-written paper. With word limits (4000 words in EVJ) it might be thought ‘wasteful’ to use valuable space with seemingly mundane information on statistical methods. Whilst it is likely that at least some explanation of statistical methods should appear within the paper, more detail can be provided in an online supplementary item if necessary. In addition to describing what statistical methods were used (and why), authors should identify which method is used where; a list of statistical tests is insufficient if the reader cannot work out, for each statistical result, which test was used. Of equal importance, authors should explain the steps they have
TABLE 1: Selected reporting guidelines Type of study
Selected guidance
Statistical analysis and reporting Studies involving experimental animals Observational epidemiological studies Randomised trials
• • • • • • • • • • • • •
Diagnostic accuracy Genetic prediction studies Economic evaluations Systematic reviews and meta-analyses Qualitative research
SAMPL ARRIVE STROBE CONSORT SPIRIT REFLECT STARD GRIPS CHEERS PRISMA MOOSE COREQ ENTREQ
http://www.equator-network.org/wp-content/uploads/2013/07/SAMPL-Guidelines-6-27-13.pdf http://www.nc3rs.org.uk/arrive-guidelines http://www.strobe-statement.org http://www.consort-statement.org http://www.spirit-statement.org http://www.reflect-statement.org/statement/ http://www.stard-statement.org Janssens et al. (2011) [2] Husereau et al. (2013) [3] http://www.prisma-statement.org Stroup et al. (2000) [4] http://intqhc.oxfordjournals.org/content/19/6/349.long http://www.biomedcentral.com/1471-2288/12/181
Many of these guidelines can be found on the EQUATOR Network website (http://www.equator-network.org). Equine Veterinary Journal 47 (2015) 131–132 © 2015 EVJ Ltd
131
Statistical guidelines
R. Christley
used to meet the assumptions underlying the statistical method and how they tested the impact of deviations from these assumptions. The guidelines provide relatively straightforward suggestions to ensure that a study’s results are presented in a clear and concise manner. The Results section should include sufficient description of the data to enable readers to understand how the authors arrived at their conclusions. This usually entails provision of estimates of effect (or difference) and measures of variation (usually the 95% confidence interval); other values may also be helpful to readers. P values may be used, but these are less informative than confidence limits, so should only be viewed as additional, rather than alternative, information. It is important that all results can be clearly linked to the methods used in their generation. As well as providing results pertinent to the question(s) at hand, this section should also provide evidence that the assumptions underlying the statistical methods have been considered and the extent to which they are met. Consideration of the limitations of a study, including the statistical analysis, should be paramount in the authors’ minds when they are writing the Discussion section and should be evident to the reader. Common flaws in statistical analyses include the following: explicit or implicit interpretation of a ‘nonsignificant’ P value to mean there is no difference between the groups; conflation of statistical significance with biological or clinical importance; failure to recognise the effect of chance, particularly when multiple statistical testing has been performed; assuming that association is the same as causation; and overinterpretation of the results, such as by inappropriate extrapolation beyond the study or by exaggerating the impact of the findings. Overall, the guidelines seek to encourage good practice and a degree of modesty in the analysis and reporting of research in EVJ. The guidelines are an important step in continued efforts to improve the quality of papers published in EVJ. As noted above, the guidelines are recommendations, not rules, and should not stifle the creativity of EVJ’s authors. They remain
a work in progress and will be updated from time to time. It is hoped that they are a useful addition for both authors and readers, even if they remain largely unnoticed (particularly by the readers of EVJ). R. Christley Statistical Editor, EVJ, Institute of Infection and Global Health, University of Liverpool, UK
References 1. International Committee of Medical Journal Editors (1997) Uniform requirements for manuscripts submitted to biomedical journals. J. Am. Med. Ass. 277, 927-934. 2. Janssens, A.C.J., Ioannidis, J.P., Duijn, C.M., Little, J. and Khoury, M.J. (2011) Strengthening the reporting of genetic risk prediction studies: the GRIPS statement. Br. Med. J. 342, d631. 3. Husereau, D., Drummond, M., Petrou, S., Carswell, C., Moher, D., Greenberg, D., Augustovski, F., Briggs, A.H., Mauskopf, J. and Loder, E. (2013) Consolidated Health Economic Evaluation Reporting Standards (CHEERS) statement. BMJ 346, f1049. http://www.ncbi.nlm.nih.gov/pubmed/23529982. Accessed November 10, 2014. 4. Stroup, D.F., Berlin, J.A., Morton, S.C., Olkin, I., Williamson, G.D., Rennie, D., Moher, D., Becker, B.J., Sipe, T.A. and Thacker, S.B. (2000) Meta-analysis of observational studies. J. Am. Med. Ass. 283, 2008-2012.
Supporting Information Additional Supporting Information may be found in the online version of this article at the publisher’s website: Supplementary Item 1: EVJ’s statistical guidelines. Supplementary Item 2: EVJ’s statistical checklist.
Equine Equin ne Veterinary eterinary eter Journal odc d Podcasts EVJs EV VJJs new Podcasts Podcast are now available to download Perfect in-car listening! Download nload ffrom iTunes iTunes https://itunes.ap https://itunes.apple.com/gb/podcast/equine-veterinary-journal/id916700720 pple.com/gb/podcast/e
or wileyonlinelibrary.com/journal/evj wileyonlinelibrary.com/journal/evj
132
Equine Veterinary Journal 47 (2015) 131–132 © 2015 EVJ Ltd
