Upstate New York Leukemia Data
Census tract level (n=281) leukemia data for the 8 counties in upstate New York from 1978-1982, paired with population data from the 1980 census. Note that 4 census tracts were completely surrounded by another unique census tract; when applying the Bayesian cluster detection model in bayes_cluster, we merge them with the surrounding census tracts yielding n=277 areas.
data(NYleukemia)
List with 5 items:
geo |
table of the FIPS code, longitude, and latitude of the geographic centroid of each census tract |
data |
table of the FIPS code, number of cases, and population of each census tract |
spatial.polygon |
object of class SpatialPolygons (See SpatialPolygons-class) containing a map of the study region |
surrounded |
row IDs of the 4 census tracts that are completely surrounded by the surrounding census tracts |
surrounding |
row IDs of the 4 census tracts that completely surround the surrounded census tracts |
http://www.sph.emory.edu/~lwaller/ch4index.htm
Turnbull, B. W. et al (1990) Monitoring for clusters of disease: application to leukemia incidence in upstate New York American Journal of Epidemiology, 132, 136–143
## Load data and convert coordinate system from latitude/longitude to grid
data(NYleukemia)
map <- NYleukemia$spatial.polygon
population <- NYleukemia$data$population
cases <- NYleukemia$data$cases
centroids <- latlong2grid(NYleukemia$geo[, 2:3])
## Identify the 4 census tract to be merged into their surrounding census tracts.
remove <- NYleukemia$surrounded
add <- NYleukemia$surrounding
## Merge population and case counts
population[add] <- population[add] + population[remove]
population <- population[-remove]
cases[add] <- cases[add] + cases[remove]
cases <- cases[-remove]
## Modify geographical objects accordingly
map <- SpatialPolygons(map@polygons[-remove], proj4string=CRS("+proj=longlat +ellps=WGS84"))
centroids <- centroids[-remove, ]
## Plot incidence in latitude/longitude
plotmap(cases/population, map, log=TRUE, nclr=5)
points(grid2latlong(centroids), pch=4)Please choose more modern alternatives, such as Google Chrome or Mozilla Firefox.