A comparison of three methods of analysis for age-period-cohort models with application to incidence data on non-Hodgkin's lymphoma.
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.
McNally
R J
RJ
Leukaemia Research Fund Centre for Clinical Epidemiology, University of Leeds, UK.
Alexander
F E
FE
Staines
A
A
Cartwright
R A
RA
D000328:Adult; D017677:Age Distribution; D000368:Aged; D000369:Aged, 80 and over; D015331:Cohort Studies; D004812:Epidemiologic Methods; D005260:Female; D006801:Humans; D015994:Incidence; D008228:Lymphoma, Non-Hodgkin / Q000453:epidemiology*; D008297:Male; D008875:Middle Aged; D015233:Models, Statistical; D017678:Sex Distribution; D006113:United Kingdom / Q000453:epidemiology