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Mortality Modeling of Partially Observed Cohorts Using Administrative Death Records

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  • Goldstein, Joshua R.
  • Osborne, Maria
  • Atherwood, Serge
  • Breen, Casey

Abstract

New advances in data linkage provide mortality researchers with access to administrative datasets with millions of mortality records and rich demographic covariates. Although these new datasets allow for high-resolution mortality research, administrative mortality records often have technical limitations, such as limited mortality coverage windows and incomplete observation of survivors. We describe a method for fitting truncated distributions that can be used for estimating mortality differentials in administrative data. We apply this method to the CenSoc datasets, which link U.S. 1940 Census records to Social Security administrative mortality records. Our approach may be useful in other contexts where administrative data on deaths are available. As a companion to the paper, we release the R package gompertztrunc, which implements the methods introduced in this paper.

Suggested Citation

  • Goldstein, Joshua R. & Osborne, Maria & Atherwood, Serge & Breen, Casey, 2022. "Mortality Modeling of Partially Observed Cohorts Using Administrative Death Records," SocArXiv efdzh, Center for Open Science.
    • Handle: RePEc:osf:socarx:efdzh
    DOI: 10.31219/osf.io/efdzh
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    References listed on IDEAS

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    1. Lior Rennert & Sharon X. Xie, 2018. "Cox regression model with doubly truncated data," Biometrics, The International Biometric Society, vol. 74(2), pages 725-733, June.
    2. Jason Fletcher & Hamid Noghanibehambari, 2024. "The effects of education on mortality: Evidence using college expansions," Health Economics, John Wiley & Sons, Ltd., vol. 33(3), pages 541-575, March.
    3. Neil K. Mehta & Irma T. Elo & Michal Engelman & Diane S. Lauderdale & Bert M. Kestenbaum, 2016. "Life Expectancy Among U.S.-born and Foreign-born Older Adults in the United States: Estimates From Linked Social Security and Medicare Data," Demography, Springer;Population Association of America (PAA), vol. 53(4), pages 1109-1134, August.
    4. Alexander, Monica, 2018. "Deaths without denominators: using a matched dataset to study mortality patterns in the United States," SocArXiv q79ye, Center for Open Science.
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