Precision of incidence predictions based on Poisson distributed observations.
T. Hakulinen, and T. Dyba. Statistics in medicine, 13 (15):
1513-23(August 1994)2440.
Abstract
Disease incidence predictions are useful for a number of administrative and scientific purposes. The simplest ones are made using trend extrapolation, on either an arithmetic or a logarithmic scale. This paper shows how approximate confidence prediction intervals can be calculated for such predictions, both for the total number of cases and for the age-adjusted incidence rates, by assuming Poisson distribution of the age and period specific numbers of incident cases. Generalizations for prediction models, for example, using power families and extra-Poisson variation, are also presented. Cancer incidence predictions for the Stockholm-Gotland Oncological Region in Sweden are used as an example.
%0 Journal Article
%1 Hakulinen1994
%A Hakulinen, T
%A Dyba, T
%D 1994
%J Statistics in medicine
%K Adult AgeFactors ConfidenceIntervals Female Forecasting Humans Incidence LinearModels Male MiddleAged Neoplasms Neoplasms:epidemiology Nonparametric PoissonDistribution Statistics Sweden Sweden:epidemiology
%N 15
%P 1513-23
%T Precision of incidence predictions based on Poisson distributed observations.
%U http://www.ncbi.nlm.nih.gov/pubmed/7973230
%V 13
%X Disease incidence predictions are useful for a number of administrative and scientific purposes. The simplest ones are made using trend extrapolation, on either an arithmetic or a logarithmic scale. This paper shows how approximate confidence prediction intervals can be calculated for such predictions, both for the total number of cases and for the age-adjusted incidence rates, by assuming Poisson distribution of the age and period specific numbers of incident cases. Generalizations for prediction models, for example, using power families and extra-Poisson variation, are also presented. Cancer incidence predictions for the Stockholm-Gotland Oncological Region in Sweden are used as an example.
@article{Hakulinen1994,
abstract = {Disease incidence predictions are useful for a number of administrative and scientific purposes. The simplest ones are made using trend extrapolation, on either an arithmetic or a logarithmic scale. This paper shows how approximate confidence prediction intervals can be calculated for such predictions, both for the total number of cases and for the age-adjusted incidence rates, by assuming Poisson distribution of the age and period specific numbers of incident cases. Generalizations for prediction models, for example, using power families and extra-Poisson variation, are also presented. Cancer incidence predictions for the Stockholm-Gotland Oncological Region in Sweden are used as an example.},
added-at = {2023-02-03T11:44:35.000+0100},
author = {Hakulinen, T and Dyba, T},
biburl = {https://www.bibsonomy.org/bibtex/200452322fb57e5ca1979e3b5a81ef15a/jepcastel},
interhash = {fb86d4d3dab29a8648c5b5cc1d4d44fb},
intrahash = {00452322fb57e5ca1979e3b5a81ef15a},
issn = {0277-6715},
journal = {Statistics in medicine},
keywords = {Adult AgeFactors ConfidenceIntervals Female Forecasting Humans Incidence LinearModels Male MiddleAged Neoplasms Neoplasms:epidemiology Nonparametric PoissonDistribution Statistics Sweden Sweden:epidemiology},
month = {8},
note = 2440,
number = 15,
pages = {1513-23},
pmid = {7973230},
timestamp = {2023-02-03T11:44:35.000+0100},
title = {Precision of incidence predictions based on Poisson distributed observations.},
url = {http://www.ncbi.nlm.nih.gov/pubmed/7973230},
volume = 13,
year = 1994
}