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Age-period-cohort modeling

Author

Listed:
  • Mark J. Rutherford

    (University of Leicester, UK)

  • Paul C. Lambert

    (University of Leicester, UK)

  • John R. Thompson

    (University of Leicester, UK)

Abstract

Age–period–cohort models provide a useful method for modeling incidence and mortality rates. It is well known that age–period–cohort models suffer from an identifiability problem due to the exact relationship between the variables (cohort = period − age). In 2007, Carstensen published an article advocating the use of an analysis that models age, period, and cohort as continuous variables through the use of spline functions (Carstensen, 2007, Statistics in Medicine 26: 3018–3045). Carstensen implemented his method for age–period–cohort models in the Epi package for R. In this article, a new command is introduced, apcfit, that performs the methods in Stata. The identifiability problem is overcome by forcing constraints on either the period or cohort effects. The use of the command is illustrated through an example relating to the incidence of colon cancer in Finland. The example shows how to include covariates in the analysis.

Suggested Citation

  • Mark J. Rutherford & Paul C. Lambert & John R. Thompson, 2010. "Age-period-cohort modeling," Stata Journal, StataCorp LP, vol. 10(4), pages 606-627, December.
    • Handle: RePEc:tsj:stataj:v:10:y:2010:i:4:p:606-627
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    References listed on IDEAS

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    1. Unknown, 1967. "Index," 1967 Conference, August 21-30, 1967, Sydney, New South Wales, Australia 209796, International Association of Agricultural Economists.
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    Cited by:

    1. Jan Baran, 2019. "Is expansion of overeducation cohort-driven? Evidence from Poland," Working Papers 2019-13, Faculty of Economic Sciences, University of Warsaw.
    2. Rutherford Mark J. & Thompson John R. & Lambert Paul C., 2012. "Projecting Cancer Incidence using Age-period-cohort Models Incorporating Restricted Cubic Splines," The International Journal of Biostatistics, De Gruyter, vol. 8(1), pages 1-27, November.

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