On Predicting Cancer Mortality using ANOVA-type P-spline Models

Authors

  • Jaione Etxeberria Public University of Navarre
  • María Dolores Ugarte Public University of Navarre
  • Tomás Goicoa Public University of Navarre
  • Ana F. Militino Public University of Navarre

DOI:

https://doi.org/10.57805/revstat.v13i1.162

Keywords:

region-specific predictions, smoothing and predicting counts, space-time interactions, prostate cancer

Abstract

Extrapolating cancer mortality trends can be very valuable as a tool to predict cancer burden. National Health Agencies use different models to figure out future evolution of cancer, but they mainly work at national level. However, developed countries are divided into different regions with their own governments and health care systems, and this should be taken into account. In this paper, an ANOVA-type P-spline model is considered to predict the number of mortality cases in forthcoming years in regions within a country. The model is very interesting as it allows to split the predictions into components representing region-specific features and characteristics common to the whole country. Prediction variability is also calculated to provide prediction intervals. Real data on cancer mortality are used for illustration.

Published

2015-04-10

How to Cite

Etxeberria, J., Ugarte , M. D., Goicoa , T., & Militino , A. F. (2015). On Predicting Cancer Mortality using ANOVA-type P-spline Models. REVSTAT-Statistical Journal, 13(1), 21–40. https://doi.org/10.57805/revstat.v13i1.162