Revistes Publicacions URV: SORT - Statistics and Operations Research Transactions> 2020

On interpretations of tests and effect sizes in regression models with a compositional predictor

  • Identification data

    Identifier: RP:4903
  • Authors:

    Pawlowsky-Glahn, Vera
    Coenders, Germà
  • Others:

    Author, as appears in the article.: Pawlowsky-Glahn, Vera Coenders, Germà
    Keywords: compositional regression models
    Abstract: Compositional data analysis is concerned with the relative importance of positive variables, expressed through their log-ratios. The literature has proposed a range of manners to compute log-ratios, some of whose interrelationships have never been reported when used as explanatory variables in regression models. This article shows their similarities and differences in interpretation based on the notion that one log-ratio has to be interpreted keeping all others constant. The article shows that centred, additive, pivot, balance and pairwise log-ratios lead to simple reparametrizations of the same model which can be combined to provide useful tests and comparable effect size estimates.
    Journal publication year: 2020
    Publication Type: ##rt.metadata.pkp.peerReviewed## info:eu-repo/semantics/publishedVersion info:eu-repo/semantics/article
  • Keywords:

    compositional regression models
  • Documents:

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