Abstract

The paper compares three different methods for performing disease incidence prediction based on simple interpolation techniques. The first method assumes that the age-period specific numbers of observed cases follow a Poisson distribution and the other two methods assume a normal distribution for the incidence rates. The main emphasis of the paper is on assessing the reliability of the three methods. For this purpose, ex post predictions produced by each method are checked for different cancer sites using data from the Cancer Control Region of Turku in Finland. In addition, the behaviour of the estimators of predicted expected values and prediction intervals, crucial for investigation of the reliability of prediction, are assessed using a simulation study. The prediction method making use of the Poisson assumption appeared to be the most reliable of the three approaches. The simulation study found that the estimator of the length of the prediction interval produced by this method has the smallest coverage error and is the most precise.

Keywords

EstimatorPoisson distributionStatisticsReliability (semiconductor)Interpolation (computer graphics)Computer scienceStandard errorPrediction intervalMathematicsArtificial intelligence

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Publication Info

Year
2000
Type
article
Volume
19
Issue
13
Pages
1741-1752
Citations
115
Access
Closed

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Tadeusz Dyba, Timo Hakulinen (2000). Comparison of different approaches to incidence prediction based on simple interpolation techniques. Statistics in Medicine , 19 (13) , 1741-1752. https://doi.org/10.1002/1097-0258(20000715)19:13<1741::aid-sim496>3.0.co;2-o

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DOI
10.1002/1097-0258(20000715)19:13<1741::aid-sim496>3.0.co;2-o