#### Send to
jQuery(document).ready( function () {
jQuery("#send_to_menu input[type='radio']").click( function () {
var selectedValue = jQuery(this).val().toLowerCase();
var selectedDiv = jQuery("#send_to_menu div." + selectedValue);
if(selectedDiv.is(":hidden")){
jQuery("#send_to_menu div.submenu:visible").slideUp();
selectedDiv.slideDown();
}
});
});
jQuery("#sendto").bind("ncbipopperclose", function(){
jQuery("#send_to_menu div.submenu:visible").css("display","none");
jQuery("#send_to_menu input[type='radio']:checked").attr("checked",false);
});

# "Magnitude-based inference": a statistical review.

### Author information

- 1
- 1Mathematical Sciences Institute, Australian National University, Canberra, Australian Capital Territory, AUSTRALIA; and 2Performance Research, Australian Institute of Sport, Belconnen, Australian Capital Territory, AUSTRALIA.

### Abstract

#### PURPOSE:

We consider "magnitude-based inference" and its interpretation by examining in detail its use in the problem of comparing two means.

#### METHODS:

We extract from the spreadsheets, which are provided to users of the analysis (http://www.sportsci.org/), 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.

#### RESULTS AND CONCLUSIONS:

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 P 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.

### Comment in

- Magnitude-based inference: progressive approach or flawed statistic? [Med Sci Sports Exerc. 2015]
- Response. [Med Sci Sports Exerc. 2015]
- The case for magnitude-based inference. [Med Sci Sports Exerc. 2015]

- PMID:
- 25051387
- PMCID:
- PMC5642352
- DOI:
- 10.1249/MSS.0000000000000451

- [Indexed for MEDLINE]