"Magnitude-based Inference". Issue 4 (April 2015)

• Record Type: Journal Article
• Authors: Welsh, Alan H.; Knight, Emma J.
• Is Part Of: Medicine and science in sports and exercise. Volume 47:Issue 4(2015)
• Publication Date: 2015-04
• Subjects: Sports medicine -- Periodicals; Exercise -- Physiological aspects -- Periodicals; Exercise -- Health aspects -- Periodicals; 612.044
• DOI: 10.1249/MSS.0000000000000451
• Languages: English
• ISSNs: 0195-9131

Abstract

<abstract> <title>ABSTRACT</title> <sec> <title>Purpose</title> <p>We consider "magnitude-based inference" and its interpretation by examining in detail its use in the problem of comparing two means.</p> </sec> <sec> <title>Methods</title> <p>We extract from the spreadsheets, which are provided to users of the analysis (<ext-link ext-link-type="uri" xlink:href="http://www.sportsci.org/" xlink:type="simple" xmlns:xlink="http://www.w3.org/1999/xlink">http://www.sportsci.org/</ext-link>), a precise description of how "magnitude-based inference" is implemented. We compare the implemented version of the method with general descriptions of it and interpret the method in familiar statistical terms.</p> </sec> <sec> <title>Results and Conclusions</title> <p>We show that "magnitude-based inference" is not a progressive improvement on modern statistics. The additional probabilities introduced are not directly related to the confidence interval but, rather, are interpretable either as <italic>P</italic> values for two different nonstandard tests (for different null hypotheses) or as approximate Bayesian calculations, which also lead to a type of test. We also discuss sample size calculations associated with "magnitude-based inference" and show that the substantial reduction in sample sizes claimed for the method (30% of the sample size obtained from standard frequentist calculations) is not justifiable so the sample size calculations should not be used. Rather than using "magnitude-based inference, " a better solution is to be realistic about the limitations of the data and use either confidence intervals or a fully Bayesian analysis.</p> </sec> </abstract>