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A simple non-linear model in incidence prediction

✍ Scribed by Tadeusz Dyba; Timo Hakulinen; Lassi Päivärinta

Publisher
John Wiley and Sons
Year
1997
Tongue
English
Weight
120 KB
Volume
16
Category
Article
ISSN
0277-6715

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✦ Synopsis

A simple model is proposed for incidence prediction. The model is non-linear in parameters but linear in time, following models in environmental cancer epidemiology. Assuming a Poisson distribution for the age and period speciÿc numbers of incident cases approximate conÿdence and prediction intervals are calculated. The major advantage of this model over current models is that age-speciÿc predictions can be made with greater accuracy. The model also preserves in the period of prediction the age pattern of incidence rates existing in the data. It may be ÿtted with any package which includes an iteratively reweighted least squares algorithm, for example GLIM. Cancer incidence predictions for the Stockholm-Gotland Oncological Region in Sweden are presented as an example.

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