Using statistics in research papers

A more flexible representation of substantive theory. Psychological Methods, 17, Click ""download paper"" below for the latest version of October 21,

Using statistics in research papers

Abstract When a statistical methods paper is submitted to a journal for publication, examples in which the method is applied to real data are highly encouraged by many journals and in some cases are explicitly demanded. In this commentary, we argue that real data examples serve several useful purposes.

However, we also argue that in many cases, particularly in the fields of genetics and genomics, there is an implicit or explicit expectation for examples to support purposes for which they are ill-suited and furthermore that these inappropriate expectations have negative consequences for the field.

We conclude by noting that real data examples can be tremendously valuable and should continue to be used where appropriate, but that the demands for, expectations of, and conclusions drawn from them need to be scaled back. Examples, Simulation, Methodology, Statistics, Genomics, Pedagogy, Publishing Statistical methods are vitally important in the biological sciences and continue to evolve.

Using statistics in research papers is nowhere more true than in genetic and genomic research. In our experience, reviewers and editors of journals that publish papers offering new statistical methods in genetics and genomics are favorably disposed to papers including a real data example that illustrates the application of the method or methods under study.

Using statistics in research papers

We believe that the inclusion of real data examples is highly desirable for reasons that we describe below. However, there also seems to be a prevailing belief on the part of many reviewers and editors, especially of high-impact journals, that a a real data example is essential, b the example should reveal an exciting biological finding, and c the method that obtains this exciting finding offers a proof of principle or validation of the method.

In contrast, we believe that each component of this tripartite belief is ill-founded and detrimental. The purpose of this commentary is to offer a more supportable perspective on the value of real data examples, to suggest greater restraint in what we ask of examples and what we conclude on their basis, and to offer guidance on using examples effectively for the purposes to which they are well suited.

First, in the past, to a large extent in textbooks as opposed to journal articles, real data examples served a key role in actually illustrating the computational steps involved in conducting certain statistical tests.

This can be invaluable as a pedagogical tool for students and works well with relatively simple calculations. Although this pedagogical tool is enormously valuable, its utility breaks down in complex situations where data sets are necessarily large, cannot be easily summarized by sufficient statistics in simple tables, and require difficult, often iterative, calculations that the reader will not be able to implement with paper and pencil.

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Hence, the value of examples to illustrate the mechanics of calculations in modern peer-reviewed articles involving genomic techniques is limited. Can be done with any example real data set. The data set need not be previously unpublished, especially interesting, or yield any particular result.

Illustrate the concept of the method and how results can be interesting. Can be done with any example real data set or for that matter a simulated data set. Inspire reader to use new method by serving as an exciting testimonial or case report of the value of the method.

This can be beneficial in promoting use but is tantamount to salesmanship rather than edification. Thus, the initial application can serve as a useful first field test of the method. Knowing that the method has been applied to real data at least once indicates that the application is practically feasible.

Third, an example can serve another pedagogical purpose, namely, conveying the concept or rationale of the proposed method and illustrating how the results obtained after applying the method can be interpreted.

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Such uses of examples not only clarify but also can make for more interesting reading. Thankfully, such purposes can be served by any example real data set or for that matter even by a simulated data set. Fourth, a real data example can provide the author with a vehicle through which to tell a story about why and how the new method should be used.

Such storytelling has been shown to help people comprehend and especially retain new ideas more effectively [ 1 ]. Finally, real data examples, when they yield biological findings that appear to be new, important, and exciting, can inspire readers to want to use the technique.

In our experience, this is a powerful form of inspiration.This article includes everything you need for writing an interesting essay: Easy technology topics with links to videos, articles, and research to start your paper.

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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.

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