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A simple non‐linear model in incidence prediction
Author(s) -
Dyba Tadeusz,
Hakulinen Timo,
Päivärinta Lassi
Publication year - 1997
Publication title -
statistics in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.996
H-Index - 183
eISSN - 1097-0258
pISSN - 0277-6715
DOI - 10.1002/(sici)1097-0258(19971030)16:20<2297::aid-sim668>3.0.co;2-f
Subject(s) - simple (philosophy) , computer science , linear model , statistics , econometrics , mathematics , machine learning , philosophy , epistemology
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 specific numbers of incident cases approximate confidence and prediction intervals are calculated. The major advantage of this model over current models is that age‐specific 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 fitted 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. © 1997 John Wiley & Sons, Ltd.