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Papers on the analysis of means (ANOM) have been circulating in the quality control literature for decades, routinely describing it as a statistical stand-alone concept. Therefore, we clarify that ANOM should rather be regarded as a special case of a much more universal approach known as multiple contrast tests (MCTs). Perceiving ANOM as a grand-mean-type MCT paves the way for implementing it in the open-source software R. We give a brief tutorial on how to exploit R's versatility and introduce the R package ANOM for drawing the familiar decision charts. Beyond that, we illustrate two practical aspects of data analysis with ANOM: firstly, we compare merits and drawbacks of ANOM-type MCTs and ANOVA F-test and assess their respective statistical powers, and secondly, we show that the benefit of using critical values from multivariate t-distributions for ANOM instead of simple Bonferroni quantiles is oftentimes negligible.

Acknowledgments

The authors would like to thank the editor and two anonymous referees for a few helpful suggestions, and Frank Schaarschmidt for his comments on an earlier version of the manuscript.

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

The work of the second author was supported by the German Research Foundation [DFG HO-1687/9].

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