inst/SpatialEpiApp/helpanalysis.md

In SpatialEpiApp: A Shiny Web Application for the Analysis of Spatial and Spatio-Temporal Disease Data

Risk estimates

Risk estimates are obtained using R-INLA, http://www.r-inla.org

|Settings: | | --- | |Spatial model: Besag et al. (1991) | |Spatio-temporal model: Bernardinelli et al. (1995) |

• Besag J, York J, Mollie A (1991). "Bayesian image restoration with applications in spatial statistics (with discussion)." Annals of the Institute of Statistical Mathemathics, 43, 1-59

• Bernardinelli L, Clayton DG, Pascutto C, Montomoli C, Ghislandi M, Songini M (1995). "Bayesian analysis of space-time variation in disease risk." Statistics in Medicine, 14, 2433-2443

• Rue H, Martino S, Chopin N (2009). "Approximate Bayesian inference for latent Gaussian models by using integrated nested Laplace approximations."Journal of the Royal Statistical Society, Series B, 71(2), 319-392

• Lindgren F, Rue H (2015). "Bayesian Spatial Modelling with R-INLA." Journal of Statistical Software, 63(19), 1-25

Detection of clusters

Detection of clusters is done using the SaTScan software. Users need to download SaTScan from http://www.satscan.org. Then, they need to install it and place the SaTScanBatch64 executable in the SpatialEpiApp/SpatialEpiApp/ss folder which is located in the R library path.

|Settings: | | --- | |Maximum population: 50% | |Monte Carlo simulations: 999 |

• Kulldorff M (1997). "A spatial scan statistic." Communications in Statistics - Theory and Methods, 26(1), 1481-1496.

• Kulldorff M (2006a). SaTScan(TM) v. 7.0. Software for the spatial and space-time scan statistics. URL http://www.satscan.org.

SpatialEpiApp documentation built on May 1, 2019, 11:16 p.m.