Issues in the mapping of two diseases

Statistical Methods in Medical Research

Volumn 14, Issue 1, 2005, Pages 83-112

  Dabney, Alan R ^a   Wakefield, Jon C ^a  

^a UNIVERSITY OF WASHINGTON   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

BLADDER CANCER; DISEASE MAPPING; EPIDEMIOLOGY; GEOGRAPHIC DISTRIBUTION; HUMAN; INCIDENCE; LUNG CANCER; MALE; MORTALITY; MOTIVATION; REVIEW; RISK ASSESSMENT; STANDARDIZATION; STATISTICAL CONCEPTS; STATISTICAL MODEL; UNITED STATES; VARIANCE;

AGED; FEMALE; HUMANS; INCIDENCE; LUNG NEOPLASMS; MALE; MODELS, STATISTICAL; PROPORTIONAL HAZARDS MODELS; URINARY BLADDER NEOPLASMS; WASHINGTON;

EID: 12744278407     PISSN: 09622802     EISSN: None     Source Type: Journal    
DOI: 10.1191/0962280205sm340oa     Document Type: Review

References (39)

1. Clayton DG, Kaldor J. Empirical Bayes estimates of age-standardized relative risks for use in disease mapping. Biometrics 1987; 43: 671-82.
2. Elliott P, Best NG. Geographical patterns of disease. In Armitage P, Colton T eds. Encyclopedia of biostatistics. London: Wiley, 1998.
3. Walter SD. Disease mapping: a historical perspective. In Elliott P, Wakefield JC, Best NG, Briggs D eds. Spatial epidemiology: methods and applications. Oxford University Press, 2000: 223-39.
4. Knorr-Held L, Best N. A shared component model for detecting joint and selective clustering of two diseases. Journal of the Royal Statistical Society: Series A 2001; 164: 73-85.
5. Clayton DG, Bernardinelli L, Montomoli C. Spatial correlation in ecological analysis. International Journal of Epidemiology 1993; 22: 1193-202.
6. Yasui Y, Potter JD, Stanford JL, Rossing MA, Winget MD, Bronner M, Daling, J. Breast cancer risk and 'delayed' primary epstein-barr virus infection. Cancer Epidemiology, Biomarkers and Prevention 2001; 10: 9-16.
7. IARC. Epstein-Barr virus and Kaposi's Sarcoma Herpesvirus/Human Herpesvirus 8, Volume 70. Iarc scientific publication, 1997.
8. Greenland S, Robins J. Ecological studies: biases, misconceptions and counterexamples. American Journal of Epidemiology 1994; 139: 747-60.
9. Morgenstern H. Ecologic study. In Armitage P, Colton T eds. Encyclopedia of biostatistics, Volume 2. Chichester, UK: Wiley and Sons Ltd, 1998: 1255-76.
10. Richardson S, Montfort C. Ecological correlation studies. In Elliott P, Wakefield JC, Best NG, Briggs D eds. Spatial epidemiology: methods and applications. New York: Oxford University Press, 2000: 205-20.
11. Wakefield JC. Sensitivity analyses for ecological regression. Biometrics 2003; 59: 9-17.
12. Cook DG, Pocock SJ. Multiple regression in geographical mortality studies, with allowance for spatially correlated errors. Biometrics 1983; 39: 361-71.
13. Wakefield JC, Morris SE. Spatial dependence and errors-in-variables in environmental epidemiology: Investigating the relationship between water constituents and heart disease. In Bernardo JM, Berger JO, Dawid AP, Smith AFM eds. Sixth Valencia international meeting on bayesian statistics. London: Oxford University Press, 1999.
14. Mollié A. Representation Geographiqu des Taux de Mortalire: Modelisation Spatiele et Methodes Bayesiennes. PhD thesis. Universite Paris 6, Paris, 1990.
15. DeSouza C. An approximate bivariate bayesian method for analyzing small frequencies. Biometrics 1992; 48: 1113-30.
16. Langford IH, Leyland AH, Rasbash J, Goldstein H. Multilevel modelling of the geographical distributions of diseases. Journal of the Royal Statistical Society, Series C (Applied Statistics) 1999; 48: 253-68.
17. Kim H, Sun D, Tsutakawa R. A bivariate bayes method for improving the estimates of mortality rates with twofold conditional autoregressive model. Journal of the American Statistical Association 2001; 96: 1506-21.
18. Cressie NAC. Statistics for spatial data, Revised Edition. New York: John Wiley, 1993.
19. Gelfand A, Vounatsou P. Proper multivariate conditional autoregressive models for spatial data analysis. Biostatistics 2003; 4: 11-25.
20. Carlin B, Banerjee S. Hierarchical multivariate car models for spatio-temporally correlated survival data. In Bernardo JM, Bayarri MJ, Dawid AP, Berger JO, Heckerman D, Smith AFM, West M eds. Seventh Valencia international meeting on bayesian statistics. London: Oxford University Press, 2003.
21. Breslow N, Day NE. Statistical methods in cancer research, Volume 2. The analysis of cohort studies. Scientific Publications No. 82. Lyon: International Agency for Research on Cancer, 1987.
22. Gail MH. The analysis of heterogeneity for indirect standardized mortality rates. Journal of the Royal Statistical Society: Series A 1978; 141: 224-34.
23. Bithell JF, Dutton SJ, Neary NM, Vincent TJ. Controlling for socioeconomic confounding using regression methods. Journal of Epidemiology and Community Health 1995; 49: S15-19.
24. Breslow NE, Clayton DG. Approximate inference in generalized linear mixed models. Journal of the American Statistical Association 1993; 88: 9-25.
25. Besag J, Green PJ, Higdon D, Mengersen K. Bayesian computation and stochastic systems (with discussion). Statistical Science 1995; 10: 3-66.
26. Moshammer H, Neuberger M. Lung cancer and dust exposure: results of a prospective cohort study following 3260 workers for 50 years. Occupational and Environmental Medicine 2004; 61: 157-62.
27. Carstairs V, Morris R. Deprivation and health in Scotland Aberdeen: Aberdeen University Press, 1991.
28. Kleinschmidt I, Hills M, Elliott P. Smoking behaviour can be predicted by neighbourhood deprivation measures. Journal of Epidemiology and Community Health 1995; 49: S72-7.
29. Besag J, York J, Mollié A. Bayesian image restoration with two applications in spatial statistics. Annals of the Institute of Statistics and Mathematics 1991; 43: 1-59.
30. Wakefield JC, Best NG, Waller LA. Bayesian approaches to disease mapping. In Elliott P, Wakefield JC, Best NG, Briggs D eds. Spatial epidemiology: methods and applications. New York: Oxford University Press, 2000: 104-27.
31. Diggle PJ, Tawn JA, Moyeed RA. Model-based geostatistics (with discussion). Applied Statistics 1998; 47: 299-350.
32. Kelsall JE, Wakefield JC. Modeling spatial variation in disease risk: a geostatistical approach. Journal of the American Statistical Association 2002; 97: 692-701.
33. Besag J, Kooperberg C. On conditional and intrinsic auto-regressions. Biometrika 1995; 82: 733-46.
34. Wakefield J, Elliott P. Issues in the statistical analysis of small area health data. Statistics in Medicine 1999; 18: 2377-99.
35. Knorr-Held L, Raßer G. Bayesian detection of clusters and discontinuities in disease maps. Biometrics 2000; 56: 13-21.
36. Rosenbaum PR, Rubin DB. Difficulties with regression analyses of age-adjusted rates. Biometrics 1984; 40: 437-43.
37. Spiegelhalter DJ, Thomas A, Best NG. Winbugs user manual, Version 1.1.1. Cambridge, UK; 1998 [www.mrc-bsu.can.ac.uk/bugs/winbugs].
38. Kelsall JE, Wakefield JC. Discussion of "Bayesian models for spatially correlated disease and exposure data" by N. Best, L. Waller, A. Thomas, E. Conlon and R. Arnold. In Bernardo JM, Berger JO, Dawid AP, Smith AFM eds. Sixth Valencia international meeting on bayesian statistics. London: Oxford University Press, 1999.
39. Price PN, Nero AV, Gelman A. Bayesian prediction of mean indoor radon concentrations for minnesota counties. Health Physics 1996; 71: 922-36.