Volume 41 - Article 42 | Pages 1205–1234  

APC curvature plots: Displaying nonlinear age-period-cohort patterns on Lexis plots

By Enrique Acosta, Alyson van Raalte


Acosta, E. (2019). Material for reproducing ‘APC Curvature Plots: Displaying nonlinear age‒period‒cohort patterns on Lexis plots’.

Download reference:

Acosta, E., Gagnon, A., Ouellette, N., van Raalte, A.A., Bourbeau, R.R., and Nepomuceno, M. (2019). Racial and ethnic diversity in the Boomers’ excess mortality due to substance abuse in the United States. Paper presented at the PAA 2019 Annual Meeting, Austin, US, April 10‒13, 2019.

Acosta, E., Hallman, S.A., Dillon, L.Y., Ouellette, N., Bourbeau, R., Herring, D.A., Inwood, K., Earn, D.J.D., Madrenas, J., Miller, M.S., and Gagnon, A. (2019). Determinants of influenza mortality trends: Age-period-cohort analysis of influenza mortality in the United States, 1959–2016. Demography 56(5): 1723–1746.

Bell, A. and Jones, K. (2013). The impossibility of separating age, period and cohort effects. Social Science and Medicine 93(Supplement C): 163–165.

Camarda, C.G. (2012). MortalitySmooth: An R package for smoothing Poisson counts with P-splines. Journal of Statistical Software .

Carstensen, B. (2007). Age‒period‒cohort models for the Lexis diagram. Statistics in Medicine 26(15): 3018–3045.

Carstensen, B., Plummer, M., Laara, E., and Hills, M. (2018). Epi: A package for statistical analysis in epidemiology.

Caselli, G. and Vallin, J. (2005). Frequency surfaces and isofrequency lines. In: Caselli, G., Vallin, J., and Wunsch, G. (eds.). Demography: Analysis and synthesis. San Diego: Academic Press: 69‒78.

Download reference:

Chauvel, L. (2013). Spécificité et permanence des effets de cohorte: Le modèle APCD appliqué aux inégalités de générations, France/États-Unis, 1985‒2010. Revue française de sociologie 54(4): 665‒705.

Chauvel, L., Leist, A., and Smith, H. (2017). Detecting the ‘Big Red Spot’ of age-period excess mortality in 25 countries: Age‒period‒cohort residual analysis. Paper presented at the PAA 2017 Annual Meeting, Chicago, US, April 27‒29, 2017.

Clayton, D. and Schifflers, E. (1987). Models for temporal variation in cancer rates. II: Age–period–cohort models. Statistics in Medicine 6(4): 469–481.

Finch, C.E. and Crimmins, E.M. (2004). Inflammatory exposure and historical changes in human life-spans. Science 305(5691): 1736–1739.

Fosse, E. and Winship, C. (2019). Analyzing age‒period‒cohort data: A review and critique. Annual Review of Sociology 45(1): 467–492.

Fosse, E. and Winship, C. (2019). Bounding analyses of age‒period‒cohort effects [unpublished manuscript]. Toronto: University of Toronto.

Fosse, E. and Winship, C. (2018). Moore–Penrose estimators of age–period–cohort effects: Their interrelationship and properties. Sociological Science 5(14): 304–334.

Goldstein, J.R. (2011). A secular trend toward earlier male sexual maturity: Evidence from shifting ages of male young adult mortality. PLOS ONE 6(8): e14826.

H.F.D. (2019). Human Fertility Database [electronic resource]. Rostock and Vienna: Max Planck Institute for Demographic Research and Vienna Institute of Demography.

H.M.D. (2019). Human Mortality Database [electronic resource]. Berkeley and Rostock: University of California, Berkeley and Max Planck Institute for Demographic Research, Rostock .

Download reference:

Hobcraft, J., Menken, J., and Preston, S. (1982). Age, period, and cohort effects in demography: A review. Population Index 48(1): 4–43.

Holford, T.R. (2005). Age‒period‒cohort analysis. Encyclopedia of Biostatistics 1: 109–126.

Holford, T.R. (1983). The estimation of age, period and cohort effects for vital rates. Biometrics 39(2): 311–324.

Holford, T.R. (1991). Understanding the effects of age, period, and cohort on incidence and mortality rates. Annual Review of Public Health 12: 425–457.

Keenan, K., Saburova, L., Bobrova, N., Elbourne, D., Ashwin, S., and Leon, D.A. (2015). Social factors influencing Russian male alcohol use over the life course: A qualitative study investigating age based social norms, masculinity, and workplace context. PLoS ONE 10(11).

Keiding, N. (2011). Age–period–cohort analysis in the 1870s: Diagrams, stereograms, and the basic differential equation. Canadian Journal of Statistics 39(3): 405–420.

Kermack, W.O., McKendrick, A.G., and McKinlay, P.L. (1934). Death-rates in Great Britain and Sweden: Some general regularities and their significance. The Lancet 223(5770): 698–703.

Keyes, K. M. and Li, G. (2010). A multiphase method for estimating cohort effects in age-period contingency table data. Annals of Epidemiology 20(10): 779–785.

Keyes, K.M., Utz, R.L., Robinson, W., and Li, G. (2010). What is a cohort effect? Comparison of three statistical methods for modeling cohort effects in obesity prevalence in the United States, 1971‒2006. Social Science and Medicine 70(7): 1100–1108.

Luo, L. (2013). Assessing validity and application scope of the intrinsic estimator approach to the age‒period‒cohort problem. Demography 50(6): 1945–1967.

Masters, R.K., Powers, D.A., Hummer, R.A., Beck, A., Lin, S.F., and Finch, B.K. (2016). Fitting age‒period‒cohort models using the intrinsic estimator: Assumptions and misapplications. Demography 53(4): 1253–1259.

Miech, R., Koester, S., and Dorsey-Holliman, B. (2011). Increasing US mortality due to accidental poisoning: the role of the baby boom cohort. Addiction 106(4): 806–815.

Munzner, T. (2014). Visualization analysis and design. Boca Raton: AK Peters/CRC Press.

Murphy, M. (2010). Reexamining the dominance of birth cohort effects on mortality. Population and Development Review 36(2): 365–390.

N.V.S.S. (2019). Bridged-race population estimates - Data files and documentation [electronic resource].

N.V.S.S. (2019). Vital statistics online data portal.

Preston, S.H. and Wang, H. (2006). Sex mortality differences in the United States: The role of cohort smoking patterns. Demography 43(4): 631–646.

Pullum, T.W. (1980). Separating age, period, and cohort effects in white U.S. fertility, 1920–1970. Social Science Research 9(3): 225–244.

Download reference:

R Core Team (2018). R: A language and environment for statistical computing.

Download reference:

Rau, R., Bohk-Ewald, C., Muszyńska, M.M., and Vaupel, J.W. (2018). Visualizing mortality dynamics in the Lexis diagram. Springer International Publishing (The Springer Series on Demographic Methods and Population Analysis).

Rau, R., Soroko, E., Jasilionis, D., and Vaupel, J.W. (2008). Continued reductions in mortality at advanced ages. Population and Development Review 34(4): 747–768.

Reither, E.N., Masters, R.K., Yang, Y.C., Powers, D.A., Zheng, H., and Land, K.C. (2015). Should age‒period‒cohort studies return to the methodologies of the 1970s? Social Science and Medicine 128: 356–365.

Remund, A., Camarda, C.G., and Riffe, T. (2018). A cause-of-death decomposition of young adult excess mortality. Demography 55(3): 957–978.

Download reference:

Remund, A., Camarda, C.G., and Riffe, T. (2017). Analyzing the young adult mortality hump in R with MortHump. Rostock: Max Planck Institute for Demographic Research, MPIDR Technical Report TR-2018-003.

Download reference:

Richards, S.J., Kirkby, J.G., and Currie, I.D. (2006). The importance of year of birth in two-dimensional mortality data. British Actuarial Journal 12(1): 5–61.

Riffe, T. (2015). Reading human fertility database and human mortality database data into R. Rostock: Max Planck Institute for Demographic Research, MPIDR Technical Report TR-2015-004.

Download reference:

Rodgers, W.L. (1982). Estimable functions of age, period, and cohort effects. American Sociological Review 47(6): 774–787.

Selvin, S. (2001). Epidemiologic analysis: A case-oriented approach. Oxford: Oxford University Press.

Tango, T. and Kurashina, S. (1987). Age, period and cohort analysis of trends in mortality from major diseases in Japan, 1955 to 1979: Peculiarity of the cohort born in the early Showa Era. Statistics in Medicine 6(6): 709–726.

Tarone, R. and Chu, K.C. (1996). Evaluation of birth cohort patterns in population disease rates. American Journal of Epidemiology 143(1): 85–91.

Tukey, J.W. (1977). Exploratory data analysis. London: Pearson.

Valdes, B. and George, K. (2013). Demographic analysis of AIDS mortality in Spain. Population 68(3): 473–485.

Wickham, H. (2016). Ggplot2: Elegant graphics for data analysis. Houston, TX: Springer International Publishing.

Willets, R.C. (2004). The cohort effect: Insights and explanations. British Actuarial Journal 10(4): 833–898.

Yang, Y. and Land, K.C. (2013). Age‒period‒cohort analysis: New models, methods, and empirical applications. Boca Raton, FL: Chapman and Hall/CRC.

Download reference:

Zang, E., Zheng, H., Yang, Y.C., and Land, K.C. (2019). Recent trends in US mortality in early and middle adulthood: Racial/ethnic disparities in inter-cohort patterns. International Journal of Epidemiology 48 (3): 934–944.

Back to the article