Space-time latent component modeling of geo-referenced health data

Statistics in Medicine

Volumn 29, Issue 19, 2010, Pages 2012-2027

  Lawson, Andrew B ^a   Song, Hae Ryoung ^b   Cai, Bo ^b   Hossainc, Md Monir ^c   Huang, Kun ^b  

^a MEDICAL UNIVERSITY OF SOUTH CAROLINA   (United States)

^b UNIVERSITY OF SOUTH CAROLINA   (United States)

^c UNIVERSITY OF TEXAS   (United States)

Author keywords

Latent; Mixture; Space time; Spatial

Indexed keywords

ARTICLE; ASTHMA; DATA ANALYSIS; EVALUATION; SIMULATION; STATISTICAL ANALYSIS; STATISTICAL MODEL;

AMBULATORY CARE FACILITIES; ASTHMA; BAYES THEOREM; COMPUTER SIMULATION; DATA INTERPRETATION, STATISTICAL; GEORGIA; HUMANS; MODELS, BIOLOGICAL; RISK FACTORS; SPACE-TIME CLUSTERING;

EID: 77955739648     PISSN: 02776715     EISSN: 10970258     Source Type: Journal    
DOI: 10.1002/sim.3917     Document Type: Article

References (31)

1. Besag J, York J, Mollié A. Bayesian image restoration with two applications in spatial statistics. Annals of the Institute of Statistical Mathematics 1991; 43:1-59.
2. Knorr-Held L. Bayesian modelling of inseparable space-time variation in disease risk. Statistics in Medicine 2000; 19:2555-2567.
3. Bernardinelli L, Clayton DG, Pascutto C, Montomoli C, Ghislandi M, Songini M. Bayesian analysis of space-time variation in disease risk. Statistics in Medicine 1995; 14:2433-2443.
4. Xia H, Carlin BP, Waller LA. Hierarchical models for mapping Ohio lung cancer rates. Environmetrics 1997; 8:107-120.
5. Knorr-Held L, Besag J. Modelling risk from a disease in time and space. Statistics in Medicine 1998; 17:2045-2060.
6. Zhu L, Carlin BP. Comparing hierarchical models for spatio-temporally misaligned data using the DIC criterion. Statistics in Medicine 2000; 19:2265-2278.
7. Mugglin A, Cressie N, Gemmel I. Hierarchical statistical modelling of influenza epidemic dynamics in space and time. Statistics in Medicine 2002; 21:2703-2721.
8. Dreassi E, Biggeri A, Catelan D. Space-time models with time-dependent covariates for the analysis of the temporal lag between socioeconomic factors and lung cancer mortality. Statistics in Medicine 2005; 24:1919-1932.
9. Richardson S, Abellan J, Best N. Bayesian spatio-temporal analysis of joint patterns of male and female lung cancer risks in Yorkshire (U.K.). Statistical Methods in Medical Research 2006; 15:97-118.
10. Martinez-Beneito M, Lopez-Quilez A, Botella-Rocamora P. An autoregressive approach to spatio-temporal disease mapping. Statistics in Medicine 2008; 27:2874-2889.
11. Hossain MM, Lawson AB. Space-time Bayesian small area disease risk models: development and evaluation with a focus on cluster detection. Environmental and Ecological Statistics 2010; 17:73-95.
12. Kottas A, Duan J, Gelfand A. Modelling disease incidence data with spatial and spatio-temporal dirichlet process mixtures. Biometrical Journal 2008; 50(2):29-42.
13. Ugarte M, Goicoa T, Ibanez B, Militano AF. Evaluating the performance of spatio-temporal Bayesian models in disease mapping. Environmetrics 2009; DOI: 10.1002/env.969.
14. Fotheringham AS, Brunsdon C, Charlton M. Geographically Weighted Regression: The Analysis of Spatially Varying Relationships. Wiley: New York, 2002.
15. Denison D, Holmes C, Mallick B, Smith A. Bayesian Methods for nonlinear Classification and Regression. Wiley: New York, 2002.
16. Wang F, Wall M. Generalized common spatial factor model. Biostatitsics 2003; 4:569-582.
17. Liu X, Wall M, Hodges J. Generalised spatial structural equation models. Biostatistics 2005; 6:539-557.
18. Tzala E, Best N. Bayesian latent variable modelling of multivariate spatio-temporal variation in cancer mortality. Statistical Methods in Medical Research 2008; 17:97-118.
19. Gelfand A, Vounatsou P. Proper multivariate conditional autoregressive models for spatial data. Biostatistics 2003; 4:11-25.
20. Dellaportas P, Forster J, Ntzoufras I. On Bayesian model and variable selection using mcmc. Statistics and Computing 2002; 12:27-36.
21. Kuo L, Mallick B. Variable selection for regression models. Sankhya 1998; 60:65-81.
22. George E, McCulloch R. Variable selection via Gibbs sampling. Journal of the American Statistical Association 1992; 79:677-683.
23. Gelman A. Prior distributions for variance parameters in hierarchical models. Bayesian Analysis 2006; 1:515-533.
24. Spiegelhalter DJ, Best NG, Carlin BP, van der Linde A. Bayesian deviance, the effective number of parameters and the comparison of arbitrarily complex models. Journal of the Royal Statistical Society B 2002; 64:583-640.
25. Celeux G, Forbes F, Robert C, Titterington M. Deviance information criteria for missing data models. Bayesian Analysis 2006; 1:651-674.
26. Plummer M. Penalized loss functions for Bayesian model comparison. Biostatistics 2008; 9:523-539.
27. Eberley L, Carlin BP. Identifiability and convergence issues for Markov chain Monte Carlo fitting of spatial models. Statistics in Medicine 2000; 19:2279-2294.
28. Bastos L, Gamerman D. Dynamical survival models with spatial frailty. Lifetime Data Analysis 2006; 12:441-460.
29. Lopes H, Salazar E, Gamerman D. Spatial dynamic factor analysis. Bayesian Analysis 2008; 3:759-792.
30. Reich B, Hodges J, Zadnik V. Effects of residual smoothing on the posterior of the fixed effects in disease-mapping models. Biometrics 2006; 62:1197-1206.
31. Ma B, Lawson AB, Liu Y. Evaluation of Bayesian models for focused clustering in health data. Environmetrics 2007; 18:1-16.