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Visualizing compositional data on the Lexis surface

Author

Listed:
  • Jonas Schöley

    (Max-Planck-Institut für Demografische Forschung)

  • Frans Willekens

    (Nederlands Interdisciplinair Demografisch Instituut (NIDI))

Abstract

Background: The Lexis surface plot is an established visualization tool in demography. Its present utility, however, is limited to the domain of one-dimensional magnitudes such as rates and counts. Visualizing proportions among three or more groups on a period-age grid is an unsolved problem. Objective: We seek to extend the Lexis surface plot to the domain of compositional data. Methods: We propose four techniques for visualizing group compositions on a period-age grid. To demonstrate the techniques we use data on age-specific cause-of-death compositions in France from 1925 to 1999. We compare the visualizations for compliance with multiple desired criteria. Results: Compositional data can effectively be visualized on the Lexis surface. A key feature of the classical Lexis surface plot – to show age, period, and cohort patterns – is retained in the domain of compositions. The optimal choice among the four proposed techniques depends primarily on the number of groups making up the composition and whether or not the plot should be readable by people with impaired colour vision. Contribution: We introduce techniques for visualizing compositional data on a period-age grid to the field of demography and demonstrate the usefulness of the techniques by performing an exploratory analysis of age-specific French cause-of-death patterns across the 20th century. We identify strengths and weaknesses of the four proposed techniques. We contribute a technique to construct the ternary-balance colour scheme from within a per- ceptually uniform colour space. Comments: A full-colour representation is key to understanding the paper. Therefore, we recommend that you read it on screen or print a colour version.

Suggested Citation

  • Jonas Schöley & Frans Willekens, 2017. "Visualizing compositional data on the Lexis surface," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 36(21), pages 627-658.
  • Handle: RePEc:dem:demres:v:36:y:2017:i:21
    DOI: 10.4054/DemRes.2017.36.21
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    References listed on IDEAS

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    1. Samuel Preston & Haidong Wang, 2006. "Sex mortality differences in The United States: The role of cohort smoking patterns," Demography, Springer;Population Association of America (PAA), vol. 43(4), pages 631-646, November.
    2. Christophe Vandeschrick, 2001. "The Lexis diagram, a misnomer," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 4(3), pages 97-124.
    3. John Aitchison & Michael Greenacre, 2002. "Biplots of compositional data," Journal of the Royal Statistical Society Series C, Royal Statistical Society, vol. 51(4), pages 375-392, October.
    4. repec:cai:popine:popu_p1990_45n2_0414 is not listed on IDEAS
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    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
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    Cited by:

    1. Ilya Kashnitsky & José Manuel Aburto, 2019. "Geofaceting: Aligning small-multiples for regions in a spatially meaningful way," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 41(17), pages 477-490.
    2. Minton, Jonathan, 2017. "Lexis Surface Visualisation Workflow," OSF Preprints ntz72_v1, Center for Open Science.
    3. Beata Nowok, 2020. "A visual tool to explore the composition of international migration flows in the EU countries, 1998–2015," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 42(27), pages 763-776.
    4. Phil Mike Jones & Jon Minton & Andrew Bell, 2023. "Methods for disentangling period and cohort changes in mortality risk over the twentieth century: comparing graphical and modelling approaches," Quality & Quantity: International Journal of Methodology, Springer, vol. 57(4), pages 3219-3239, August.
    5. Schöley, Jonas & Kashnitsky, Ilya, 2019. "But Why? Design choices made while creating "Regional population structures at a glance"," OSF Preprints qt47d, Center for Open Science.
    6. Breen, Casey & Goldstein, Joshua R., 2022. "Berkeley Unified Numident Mortality Database: Public Administrative Records for Individual-Level Mortality Research," SocArXiv pc294_v1, Center for Open Science.
    7. Jorge Cimentada & Sebastian Kluesener & Tim Riffe, 2020. "Exploring the demographic history of populations with enhanced Lexis surfaces," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 42(6), pages 149-164.
    8. Cimentada, Jorge & Klüsener, Sebastian & Riffe, Tim, 2019. "Exploring the Demographic History of Populations with Enhanced Lexis Surfaces," SocArXiv hxy7d, Center for Open Science.
    9. Breen, Casey & Goldstein, Joshua R., 2022. "Berkeley Unified Numident Mortality Database: Public Administrative Records for Individual-Level Mortality Research," SocArXiv pc294, Center for Open Science.
    10. Cimentada, Jorge & Klüsener, Sebastian & Riffe, Tim, 2019. "Exploring the Demographic History of Populations with Enhanced Lexis Surfaces," SocArXiv hxy7d_v1, Center for Open Science.
    11. Tim Riffe & José Manuel Aburto, 2020. "Lexis fields," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 42(24), pages 713-726.
    12. Jonas Schöley, 2021. "The centered ternary balance scheme: A technique to visualize surfaces of unbalanced three-part compositions," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 44(19), pages 443-458.
    13. Schöley, Jonas & Kashnitsky, Ilya, 2019. "But Why? Design choices made while creating "Regional population structures at a glance"," OSF Preprints qt47d_v1, Center for Open Science.
    14. Timothy Riffe & José M. Aburto, 2019. "Lexis fields," MPIDR Working Papers WP-2019-001, Max Planck Institute for Demographic Research, Rostock, Germany.
    15. Minton, Jonathan, 2017. "Lexis Surface Visualisation Workflow," OSF Preprints ntz72, Center for Open Science.

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    More about this item

    Keywords

    data visualization; mortality; cause of death; France; compositional data; Lexis surface; color scale;
    All these keywords.

    JEL classification:

    • J1 - Labor and Demographic Economics - - Demographic Economics
    • Z0 - Other Special Topics - - General

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