Proportionality: A Valid Alternative to Correlation for Relative Data

David Lovell; Vera Pawlowsky-Glahn; Juan José Egozcue; Samuel Marguerat; Jürg Bähler

doi:10.1371/journal.pcbi.1004075

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Open Access

Peer-reviewed

Research Article

Proportionality: A Valid Alternative to Correlation for Relative Data

David Lovell ,

* E-mail: David.Lovell@qut.edu.au

Affiliation Queensland University of Technology, Brisbane, Australia
⨯
Vera Pawlowsky-Glahn,

Affiliation Dept. d’Informàtica, Matemàtica Aplicada i Estadística. U. de Girona, España
⨯
Juan José Egozcue,

Affiliation Dept. Applied Mathematics III, U. Politécnica de Catalunya, Barcelona, Spain
⨯
Samuel Marguerat,

Affiliation MRC Clinical Sciences Centre, Imperial College London, United Kingdom
⨯
Jürg Bähler

Affiliation Research Department of Genetics, Evolution and Environment, University College London, United Kingdom
⨯

Proportionality: A Valid Alternative to Correlation for Relative Data

David Lovell,
Vera Pawlowsky-Glahn,
Juan José Egozcue,
Samuel Marguerat,
Jürg Bähler

Published: March 16, 2015
https://doi.org/10.1371/journal.pcbi.1004075
See the preprint

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Scaling log-ratio variance

Posted by ionase on 18 Jan 2016 at 09:31 GMT

The scaling of log-ratio variance proposed here, when applied on relative data, can lead to inconsistencies with results obtained on absolute data. For details see our article

http://link.springer.com/...

No competing interests declared.

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Proportionality: A Valid Alternative to Correlation for Relative Data

Proportionality: A Valid Alternative to Correlation for Relative Data

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Scaling log-ratio variance

Posted by ionase on 18 Jan 2016 at 09:31 GMT