title: A simple non-linear model in incidence prediction.
abstract: 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.
authors.affiliation: Finnish Cancer Registry, Helsinki, Finland.
authors.forename: T
authors.initials: T
authors.lastname: Dyba
authors.forename: T
authors.initials: T
authors.lastname: Hakulinen
authors.forename: L
authors.initials: L
authors.lastname: Päivärinta
mesh_terms: D000328:Adult; D000367:Age Factors; D000368:Aged; D016001:Confidence Intervals; D005260:Female; D005544:Forecasting; D006801:Humans; D015994:Incidence; D016013:Likelihood Functions; D008875:Middle Aged; D015233:Models, Statistical; D009369:Neoplasms / Q000453:epidemiology*; D016012:Poisson Distribution; D013548:Sweden / Q000453:epidemiology