International Journal of Epidemiology, Vol 26, 32-46, Copyright © 1997 by International Epidemiological Association
RJ McNally, FE Alexander, A Staines and RA Cartwright
BACKGROUND: Various methods of analysis have been used to study age-
period-cohort models. The main aim of this paper is to illustrate and
compare three such methods. Those of Clayton and Schifflers, Robertson and
Boyle, and De Carli and La Vecchia. The main differences between these
methods lie in their approach to distinguish between linear- period and
linear-cohort effects. Clayton and Schifflers do not attempt to solve this
identification problem, whereas Robertson and Boyle, and De Carli and La
Vecchia attempt to tackle this question. METHODS: In order to study the
assumptions and problems of these methods, we analysed data from 2678
subjects aged 30-84 in Yorkshire, UK, who were diagnosed with non-Hodgkin's
lymphoma (NHL) during the period 1978- 1991. Loglinear Poisson models were
used to examine the effects of age, period and cohort. RESULTS: All three
methods of analysis agree that, after stratification for sex and county,
the age-standardized rate has been increasing at about 5% per year. The
Robertson-Boyle method differed from the Clayton-Schifflers method in
showing a significant non-linear cohort effect, and a significant
county-cohort interaction. The method of De Carli-La Vecchia agreed more
closely with Clayton- Schifflers than with Robertson-Boyle. CONCLUSIONS:
The linear increase in incidence would lead to a doubling of the number of
cases within 15 years. There is controversy over whether the identification
problem can be solved and should be solved. Many authors would not rely on
the results of the methods of Robertson and Boyle, or De Carli and La
Vacchia.
ARTICLES
A comparison of three methods of analysis for age-period-cohort models with application to incidence data on non-Hodgkin's lymphoma
Leukaemia Research Fund Centre for Clinical Epidemiology, University of Leeds, UK.
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