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
Affiliated Institutions
Related Publications
A Modified Poisson Regression Approach to Prospective Studies with Binary Data
Relative risk is usually the parameter of interest in epidemiologic and medical studies. In this paper, the author proposes a modified Poisson regression approach (i.e., Poisson...
Fast Stable Restricted Maximum Likelihood and Marginal Likelihood Estimation of Semiparametric Generalized Linear Models
Summary Recent work by Reiss and Ogden provides a theoretical basis for sometimes preferring restricted maximum likelihood (REML) to generalized cross-validation (GCV) for smoot...
Confidence Limits for the Indirect Effect: Distribution of the Product and Resampling Methods
The most commonly used method to test an indirect effect is to divide the estimate of the indirect effect by its standard error and compare the resulting z statistic with a crit...
Testing for a Finite Mixture Model with Two Components
Summary We consider a finite mixture model with k components and a kernel distribution from a general one-parameter family. The problem of testing the hypothesis k=2 versusk⩾3 i...
Direct and Indirect Effects: Classical and Bootstrap Estimates of Variability
The decomposition of effects in structural equation models has been of considerable interest to social scientists. Finite-sample or asymptotic results for the sampling distribut...
Publication Info
- Year
- 2000
- Type
- article
- Volume
- 19
- Issue
- 13
- Pages
- 1741-1752
- Citations
- 115
- Access
- Closed
External Links
Social Impact
Social media, news, blog, policy document mentions
Citation Metrics
Cite This
Identifiers
- DOI
- 10.1002/1097-0258(20000715)19:13<1741::aid-sim496>3.0.co;2-o