MAGIC criteria

Short description: Set of guidelines for using statistical analysis

The MAGIC criteria are a set of guidelines put forth by Robert Abelson in his 1995 book Statistics as Principled Argument.[1] In this book he posits that the goal of statistical analysis should be to make compelling claims about the world[2] and he presents the MAGIC criteria as a way to do that.

## Contents

* 1 What are the MAGIC criteria?
* 2 Reviews and applications of the MAGIC criteria
* 3 See also
* 4 References

## What are the MAGIC criteria?

MAGIC is a backronym for:

1. Magnitude – How big is the effect? Large effects are more compelling than small ones.
2. Articulation – How specific is it?[3] Precise statements are more compelling than imprecise ones.
3. Generality – How generally does it apply?[2] More general effects are more compelling than less general ones. Claims that would interest a more general audience are more compelling.[3]
4. Interestingness – interesting effects are those that "have the potential, through empirical analysis, to change what people believe about an important issue".[2] More interesting effects are more compelling than less interesting ones. In addition, more surprising effects are more compelling than ones that merely confirm what is already known.[3]
5. Credibility – Credible claims are more compelling than incredible ones. The researcher must show that the claims made are credible.[2] Results that contradict previously established ones are less credible.[3]

## Reviews and applications of the MAGIC criteria

Song Qian noted that the MAGIC criteria could be of use to ecologists.[4] Claudia Stanny discussed them in a course on psychology.[5] Anne Boomsma noted that they are useful when presenting results of complex statistical methods such as structural equation modelling.[6]

## See also

* Philosophy:Bradford Hill criteria - Criteria for measuring cause and effect

## References

1. ↑ Abelson, Robert P. (1995). Statistics as principled argument. Internet Archive. Hillsdale, N.J. : L. Erlbaum Associates. ISBN 978-0-585-17659-8. http://archive.org/details/statisticsasprin0000abel.
2. ↑ 2.0 2.1 2.2 2.3 "The MAGIC Criteria". jsvine.com. 16 February 2015. http://drafts.jsvine.com/the-magic-criteria/. Retrieved 13 February 2020.
3. ↑ 3.0 3.1 3.2 3.3 "Criteria for a persuasive statistical argument: MAGIC". Simon Fraser University. https://www2.cs.sfu.ca/CourseCentral/376/ted/376-08-1/MAGIC-criteria.pdf. Retrieved 13 February 2020. "Adapted from Abelson, Robert P. (1995). Statistics as principled argument. Hillsdale, NJ: Lawrence Erlbaum, pp. 12–14."
4. ↑ Qian, Song (2014). "Statistics in ecology is for making a "principled argument"". Landscape Ecology 29 (6): 937–939. doi:10.1007/s10980-014-0042-y.
5. ↑ Caludia, Stanny. "404 – Page Not Found | University of West Florida". http://uwf.edu/cstanny/website/ResearchDsgn/statistical claims abelson 1&2 - 3 slides.pdf.
6. ↑ Boomsma, Anne (2000). "Reporting Analysis of Covariance Studies". Structural Equation Modeling 7: 461–483. doi:10.1207/S15328007SEM0703_6.

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