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Compositional data analysis tutorial.

Michael Smithson1, Stephen B Broomell2

  • 1Research School of Psychology, Australian National University.

Psychological Methods
|January 31, 2022
PubMed
Summary
This summary is machine-generated.

This study introduces methods for analyzing compositional data, which sums to a constant. These techniques, including established and novel approaches, enable researchers to gain new insights from psychological and social science datasets.

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Area of Science:

  • Psychology
  • Social Sciences
  • Data Analysis

Background:

  • Compositional (ipsative) data, where values sum to a constant, are common in psychological research.
  • Analysis of such data was limited historically due to a lack of appropriate statistical methods.
  • Despite past challenges, compositional data analysis offers unique insights.

Purpose of the Study:

  • To present techniques for analyzing compositional data.
  • To demonstrate the application of these methods to real-world social science data.
  • To enable researchers to effectively analyze ipsative datasets.

Main Methods:

  • Elaboration of the technical details of compositional data.
  • Discussion of established and novel analytical approaches.
  • Application of methods to social science datasets with accompanying R code.

Main Results:

  • Demonstration that converting data to a compositional form can yield previously inaccessible insights.
  • Successful application of presented techniques to real data.
  • Identification of current state-of-the-art and remaining challenges in compositional data analysis.

Conclusions:

  • Sound methods for analyzing compositional data are available and presented.
  • The study facilitates the analysis of ipsative scales in psychological research.
  • Resources for compositional data analysis, including software, are provided.