Cluster detection based on spatial associations and iterated residuals in generalized linear mixed models

Biometrics

Volumn 65, Issue 2, 2009, Pages 353-360

  Zhang, Tonglin ^a   Lin, Ge ^b  

^a PURDUE UNIVERSITY   (United States)

^b WEST VIRGINIA UNIVERSITY   (United States)

Author keywords

Generalized linear models; Local clusters; Mixed effects; Moran's I statistic; Pearson residuals; Spatial heterogeneity

Indexed keywords

STATISTICAL TESTS;

GENERALIZED LINEAR MIXED-EFFECTS MODELS; GENERALIZED LINEAR MODEL; LOCAL CLUSTER; MIXED EFFECTS; MORAN I; MORAN I STATISTIC; PEARSON RESIDUAL; SPATIAL ASSOCIATIONS; SPATIAL CLUSTER; SPATIAL HETEROGENEITY;

BAYESIAN NETWORKS;

BAYESIAN ANALYSIS; CLUSTER ANALYSIS; DETECTION METHOD; HETEROGENEITY; MODELING; SPATIAL DISTRIBUTION; SPATIAL VARIATION;

ARTICLE; BAYES THEOREM; CANCER MORTALITY; CLUSTER ANALYSIS; COLORECTAL CANCER; HUMAN; MATHEMATICAL MODEL; METHODOLOGY; MONTE CARLO METHOD; PARAMETERS OF MEASUREMENT AND ANALYSIS; POPULATION SIZE; UNITED STATES;

EID: 66949140339     PISSN: 0006341X     EISSN: 15410420     Source Type: Journal    
DOI: 10.1111/j.1541-0420.2008.01069.x     Document Type: Article

References (18)

1. Agresti, A. (2002). Categorical Data Analysis. New York : Wiley.
2. Assuncao, R. and Reis, E. (1999). A new proposal to adjust Moran's I for population density. Statistics in Medicine 18, 2147 2162. (Pubitemid 29408257)
3. Baddeley, A., Turner, R., Moller, J., and Hazelton, M. (2005). Residual analysis for spatial point processes (with discussion). Journal of the Royal Statistical Society, Series B 67, 617 666.
4. Cliff, A. D. and Ord, J. K. (1981). Spatial Processes: Models and Applications. London : Pion.
5. Gangnon, R. E. and Clayton, M. K. (2003). A hierarchical model for spatially clustered disease rates. Statistics in Medicine 22, 3213 3228. (Pubitemid 37220628)
6. Jacqmin-Gadda, H., Commenges, D., Nejjari, C., and Dartigues, J. (1997). Tests of geographical correlation with adjustment for explanatory variables: An application to dyspnoea in the elderly. Statistics in Medicine 16, 1283 1297. (Pubitemid 27252597)
7. Kleinman, K. (2005). Generalized linear models and generalized linear mixed models for small-area surveillance. In Spatial and Syndromic Surveillance for Public Health, A. B. Lawson and K. Kleinman (eds 77 93. London : Wiley.
8. Kulldorff, M. (1997). A spatial scan statistic. Communications in Statistics, Theory and Methods 26, 1481 1496. (Pubitemid 127447921)
9. Lawson, A. B. and Clark, A. (2002). Spatial mixture relative risk models applied to disease mapping. Statistics in Medicine 21, 359 370. (Pubitemid 34144647)
10. Lin, G. (2003). A spatial logit association model for cluster detection. Geographical Analysis 35, 329 340. (Pubitemid 37379542)
11. Lin, G. and Zhang, T. (2007). Loglinear residual tests of Moran's I autocorrelation: An application to Kentucky breast cancer incidence data. Geographical Analysis 39, 293 310. (Pubitemid 46930054)
12. Loh, J. M. and Zhu, Z. (2007). Accounting for spatial correlation in the scan statistic. Annals of Applied Statistics 1, 560 584.
13. McCulloch, C. E. (1997). Maximum likelihood algorithms for generalized linear mixed models. Journal of the American Statistical Association 92, 162 170.
14. Moran, P. A. P. (1948). The interpretation of statistical maps. Journal of the Royal Statistical Society, Series B 10, 243 251.
15. Roche, L. S., Skinner, R., and Weinstein, R. B. (2002). Use of a geographic information system to identify and characterize areas with high proportions of distant stage breast cancer. Journal of Public Health Management Practice 8, 26 32.
16. Waller, L. and Gotway, C. (2004). Applied Spatial Statistics for Public Health Data. Hoboken, New Jersey : Wiley.
17. Zeger, S. L. (1988). A regression model for time series of counts. Biometrika 75, 621 629.
18. Zhuang, J. (2006). Second-order residual analysis of spatiotemporal point processes and applications in model evaluation. Journal of the Royal Statistical Society, Series B 68, 635 653. (Pubitemid 44092349)