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Comparison of Four Methods for Estimating Complete Life Tables from Abridged Life Tables Using Mortality Data Supplied to EUROCARE-3

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  • P. Baili
  • A. Micheli
  • A. Montanari
  • R. Capocaccia

Abstract

To estimate mortality due to cancer, it is necessary to have mortality data by year of age in the population of cancer patients. When such data are not available, estimating one-year (complete) life tables from five-year (abridged) life tables is necessary. Four such methods—Elandt-Johnson, Kostaki, Brass logit, and Akima spline methods—are compared with respect to 782 empirical complete life tables pertaining to 19 European regions or countries, from 1954 to 2000. Abridged life tables are first derived from the empirical ones, then used to produce one-year-life tables by each of the four methods. These reconstituted complete life tables are then compared with the empirical complete life tables. Among the four methods, the Elandt-Johnson demographic method produces the best reconstitutions at adult ages, specifically those ages at which observed cancer survival needs to be corrected.

Suggested Citation

  • P. Baili & A. Micheli & A. Montanari & R. Capocaccia, 2005. "Comparison of Four Methods for Estimating Complete Life Tables from Abridged Life Tables Using Mortality Data Supplied to EUROCARE-3," Mathematical Population Studies, Taylor & Francis Journals, vol. 12(4), pages 183-198.
    • Handle: RePEc:taf:mpopst:v:12:y:2005:i:4:p:183-198
    DOI: 10.1080/08898480500301751
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    References listed on IDEAS

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    1. Anastasia Kostaki & Vagelis Panousis, 2001. "Expanding an abridged life table," Demographic Research, Max Planck Institute for Demographic Research, Rostock, Germany, vol. 5(1), pages 1-22.
    2. Anastasia Kostaki, 2000. "A relational technique for estimating the age-specific mortality pattern from grouped data," Mathematical Population Studies, Taylor & Francis Journals, vol. 9(1), pages 83-95.
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    Cited by:

    1. Soumya Pal & Abhishek Singh & Kaushalendra Kumar, 2022. "Inequality in length of life in India: an empirical analysis," Journal of Population Research, Springer, vol. 39(3), pages 315-340, September.
    2. Pal, Soumya, 2022. "Length of Life Inequality in India: An Empirical Analysis," SocArXiv 3kwtq, Center for Open Science.
    3. Sigurd Dyrting & Andrew Taylor & Tom Wilson, 2024. "Application of P-TOPALS for Smoothing Input Data for Population Projections ‘At the Edge’," Population Research and Policy Review, Springer;Southern Demographic Association (SDA), vol. 43(2), pages 1-28, April.

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