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    Rights statement: This is an Accepted Manuscript of an article published by Taylor & Francis Group in Journal of Applied Statistics on 12/02/2016, available online: http://www.tandfonline.com/10.1080/02664763.2015.1117584

    Accepted author manuscript, 454 KB, PDF document

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Analysis of means: a generalized approach using R

Research output: Contribution to journalJournal articlepeer-review

Published
<mark>Journal publication date</mark>2016
<mark>Journal</mark>Journal of Applied Statistics
Issue number8
Volume43
Number of pages20
Pages (from-to)1541-1560
Publication StatusPublished
Early online date12/02/16
<mark>Original language</mark>English

Abstract

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 opensource software R. We give a brief tutorial on how to exploit R's versatility and introduce R package ANOM for drawing the familiar decision charts. Beyond that, we illustrate two practical aspects of data analysis with ANOM: rstly, 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 benet of using critical values from multivariate t-distributions for ANOM instead of simple Bonferroni quantiles is oftentimes negligible.

Bibliographic note

This is an Accepted Manuscript of an article published by Taylor & Francis Group in Journal of Applied Statistics on 12/02/2016, available online: http://www.tandfonline.com/10.1080/02664763.2015.1117584