Q2q: An R Package for Interpolating Age-Specific Mortality Rates at All Ages

Farid Flici

doi:10.5334/jors.484

Abstract

Q2q is a R package that simplifies the interpolation of age-specific mortality rates across all ages, starting from abridged life-tables. Due to differences in the age-patterns of mortality rates at juvenile and adult ages, it is challenging to identify a unique method to interpolate mortality rates at both age categories with sufficient quality. Typically, the six-term interpolation formula of Lagrange and the Karup king formula are used for younger and older ages, respectively. The Q2q package combines the two methods, with a junction point defined as the point where the two obtained mortality curves are the closest possible. The package is publicly accessible on CRAN and Github, and may be used for both annual and multi-annual data.

References

Kimball AW. Estimation of mortality intensities in animal experiments. Biometrics. 1960;16(4):505–521. DOI: 10.2307/2527758
Open DOI Search in Google Scholar Back to article
Wilmoth JR, Andreev K, Jdanov D, Glei DA, Boe C, Bubenheim M, Philipov D, Shkolniko V, Vachon P. Methods protocol for the human mortality database, 5th Edition, University of California, Berkeley, and Max Planck Institute for Demographic Research, Rostock, 2007, http://www.mortality.org/Public/Docs/MethodsProtocol.pdf.
Search in Google Scholar Back to article
Gavrilov LA, Gavrilova NS. Mortality measurement at advanced ages: a study of the Social Security Administration Death Master File. North American actuarial journal. 2011;15(3):432–447. DOI: 10.1080/10920277.2011.10597629
Open DOI Search in Google Scholar Back to article
Heligman L, Pollard JH. The age pattern of mortality. Journal of the Institute of Actuaries. 1980;107(1):49–80. DOI: 10.1017/S0020268100040257
Open DOI Search in Google Scholar Back to article
Kostaki A. The Heligman-Pollard formula as a tool for expanding an abridged life table. Journal of Official Statistics. 1991;7(3):311–323.
Search in Google Scholar Back to article
Li N. Estimating Complete Life Tables for Populations with Limited Size: From Graduation to Equivalent Construction. North American Actuarial Journal. 2020;24(1):22–35. DOI: 10.1080/10920277.2019.1585879
Open DOI Search in Google Scholar Back to article
Kostaki A, Panousis V. Expanding an abridged life table. Demographic Research. 2001;5:1–22. DOI: 10.4054/DemRes.2001.5.1
Open DOI Search in Google Scholar Back to article
Shryock HS, Siegel JS, Associates. Interpolation: Selected General Methods. In: Bogue DJ, Arriaga EE, Anderton DL, Rumsey GW (Eds.), Readings in Population Research Methodology. Vol. 1: Basic Tools, Social Development Center/UN Population Fund, 1993;5-48–5-72.
Search in Google Scholar Back to article
Elandt-Johnson RC, Johnson NL. Survival models and data analysis. Wiley Online Library; 1980. DOI: 10.1080/03461238.1980.10408643
Open DOI Search in Google Scholar Back to article
Gompertz B. On the nature of the function expressive of the law of human mortality, and on a new mode of determining the value of life contingencies. Philosophical transactions of the Royal Society of London. 1825;115:513–583. DOI: 10.1098/rstl.1825.0026
Open DOI Search in Google Scholar Back to article
Wickham H. Testthat: Get started with testing. R Journal. 2011;3(1):5–10. DOI: 10.32614/RJ-2011-002
Open DOI Search in Google Scholar Back to article

Q2q: An R Package for Interpolating Age-Specific Mortality Rates at All Ages

Abstract

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