IDEAS home Printed from https://ideas.repec.org/a/pal/palcom/v2y2016i1d10.1057_palcomms.2015.49.html
   My bibliography  Save this article

How much can we trust life tables? Sensitivity of mortality measures to right-censoring treatment

Author

Listed:
  • Trifon I Missov

    (Max Planck Institute for Demographic Research, Rostock, Germany
    Institute of Sociology and Demography, University of Rostock, Rostock, Germany)

  • László Németh

    (Max Planck Institute for Demographic Research, Rostock, Germany)

  • Maciej J Dańko

    (Max Planck Institute for Demographic Research, Rostock, Germany)

Abstract

International organizations, research institutions, insurance companies, pension funds and health policymakers calculate human mortality measures from life tables. Life-table data, though, are usually right-censored; that is, the last open-end age group does not contain information about the exact ages at death of individuals there and mortality measures are sensitive to the way censoring is addressed. The standard way of “closing” the life table assumes a constant hazard of death for the last age group. This might lead to erroneous conclusions about mortality measures, especially when the open-end age interval contains a large proportion of the study population. In this article, we propose, instead, fitting a parametric model that well describes human mortality patterns, the gamma-Gompertz-Makeham, accounting for censoring and constructing model-based equivalents of five mortality measures: life expectancy, the modal age at death, life disparity, entropy and the Gini coefficient. We show that, in comparison to conventional life-table measures, model-based measures are less sensitive to the age at censoring or, equivalently, to the proportion of censored individuals and can be only slightly distorted even if the age at censoring is low. This study also compares life-table and model-based mortality measures for a non-human population with an underlying Gompertz mortality schedule in which a fixed proportion of the population is censored. Using model-based mortality measures is essential when studying the mortality of populations subjected to substantial censoring; for instance, many life tables for developing countries contain an open-end interval that contains more than 10% of the population. In this study, we show that life expectancy at birth for Brazilian females in 2007, calculated by standard life-table algebra, exceeds by almost 3 years the gamma-Gompertz-Makeham model-based life expectancy. This article might serve as a basis for recalculation of mortality measures for all populations subjected to substantial censoring.

Suggested Citation

  • Trifon I Missov & László Németh & Maciej J Dańko, 2016. "How much can we trust life tables? Sensitivity of mortality measures to right-censoring treatment," Palgrave Communications, Palgrave Macmillan, vol. 2(1), pages 1-10, December.
  • Handle: RePEc:pal:palcom:v:2:y:2016:i:1:d:10.1057_palcomms.2015.49
    DOI: 10.1057/palcomms.2015.49
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/palcomms.2015.49
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1057/palcomms.2015.49?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    Citations

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


    Cited by:

    1. Filipe Costa Souza & Wilton Bernardino & Silvio C. Patricio, 2024. "How life-table right-censoring affected the Brazilian social security factor: an application of the gamma-Gompertz-Makeham model," Journal of Population Research, Springer, vol. 41(3), pages 1-38, September.
    2. Dalkhat M. Ediev, 2018. "Constrained Mortality Extrapolation to Old Age: An Empirical Assessment," European Journal of Population, Springer;European Association for Population Studies, vol. 34(3), pages 441-457, August.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:pal:palcom:v:2:y:2016:i:1:d:10.1057_palcomms.2015.49. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    We have no bibliographic references for this item. You can help adding them by using this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: https://www.nature.com/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.