A hierarchical Bayesian model for space-time variation of disease risk

Statistical Modelling

Volumn 1, Issue 1, 2001, Pages 17-29

  Lagazio, Corrado ^a   Dreassi, Emanuela ^b   Biggeri, Annibale ^b  

^a UNIVERSITY OF UDINE   (Italy)

^b UNIVERSITY OF FLORENCE   (Italy)

Author keywords

cohort effects; hierarchiical Bayesian model; space time analysis

Indexed keywords

EID: 84993815519     PISSN: 1471082X     EISSN: None     Source Type: Journal    
DOI: 10.1177/1471082X0100100103     Document Type: Article

References (20)

1. Assunçao R.M., Reis I.A., Di Lorenzo Oliveira C. (2000) Diffusion and prediction of Leishmaniasis in a large metropolitan area in Brazil with a Bayesian space-time model. Web page http://www.est.ufmg.br/%7Eassuncao/art/art.html, e-mail: assuncao@est.ufmg.br
2. Bernardinelli L., Clayton D., Pascutto C., Montomoli C. et al. (1995) Bayesian analysis of space-time variation in disease risk. Statistics in Medicine 14, 2433-2443.
3. Besag J., York J., Mollie A. (1991) Bayesian image restoration, with two applications in spatial statistics (with discussion). Annals of the Institute of Statistical Mathematics 43, 1-59.
4. Clayton D., Schifflers E. (1987 a) Models for temporal variation in cancer rates. I: age-period and age-cohort models. Statistics in Medicine 6, 449-467.
5. Clayton D., Schifflers E. (1987 b) Models for temporal variation in cancer rates. II: age-period-cohort models. Statistics in Medicine 6, 469-481.
6. Clayton D. (1996) Generalized linear mixed models. In: Gilks W.R., Richardson S., Spiegelhalter D.J., eds. Markov Chain Monte Carlo in practice. London: Chapman and Hall, 275-301.
7. Gelman A., Rubin D.R. (1992) Inference from iterative simulation using multiple sequences (with discussion). Statistical Science 7, 457-511.
8. Kass R.E., Raftery A.E. (1995) Bayes factors. Journal of the American Statistical Association 90, 773-795.
9. Knorr-Held L., Besag J. (1998) Modelling risk from a disease in time and space. Statistics in Medicine 17, 2045-2060.
10. Knorr-Held L. (2000 a) Bayesian modelling of inseparable space-time variation in disease risk. Statistics in Medicine 19, 2555-2568.
11. Knorr-Held L. (2000 b) Prognosis of lung cancer mortality in West Germany. A case study in Bayesian prediction. Biostatistics (to appear).
12. Lilienfeld A.M., Lilienfeld D.E. (1980) Foundations of epidemiology. New York: Oxford University Press.
13. Lopez-Abente G., Pollan M., de la Iglesia P., Ruiz M. (1995) Characterization of the lung cancer epidemic in the European Union (1970-1990). Cancer Epidemiology Biomarkers and Prevention 4(8), 813-820.
14. Mason T.J., McKay F.W., Hoover R., Blot W.J. et al. (1975) Atlas of cancer mortality for US Counties: 1950-1969, Washington: USGPO.
15. Mayer J.D. (1983) The role of spatial analysis and geographic data in the detection of disease causation. Social Science and Medicine 17(16), 1213-1221.
16. Spiegelhalter D.J., Best N.G., Carlin B.P. (1998) Bayesian deviance, the effective number of parameters, and the comparison of arbitrarily complex models. Research Report 98-009, Division of Biostatistics, University of Minnesota.
17. Spiegelhalter D.J., Thomas A., Best N.G., Gilks W.R. (2000) WinBUGS. Medical Research Council Biostatistics Unit, Cambridge.
18. Sun D., Tsutakawa R.K., Kim H., He Z. (2000) Spatio-temporal interaction with disease mapping. Statistics in Medicine 19, 2015-2035.
19. Vigotti M.A., Biggeri A., Dreassi E., Baccini M. et al. (1999) Atlas of mortality in Tuscany 1971-94. Proceedings of the XV international scientific meeting of the international epidemiological association ‘Epidemiology for sustainable health’, vol. 1, p 200-210.
20. Waller L.A., Carlin B.P., Xia H., Gelfand A.E. (1997) Hierarchical spatio-temporal mapping of disease rates. Journal of the American Statistical Association 92, 607-617.