Description Usage Format Details Source References Examples
New York leukemia data taken from the data sets supporting Waller and Gotway 2004 (the data should be loaded by running example(NY_data) to demonstrate spatial data import techniques).
1  | 
A data frame with 281 observations on the following 12 variables, and the binary coded spatial weights used in the source.
AREANAMEname of census tract
AREAKEYunique FIPS code for each tract
Xx-coordinate of tract centroid (in km)
Yy-coordinate of tract centroid (in km)
POP8population size (1980 U.S. Census)
TRACTCASnumber of cases 1978-1982
PROPCASproportion of cases per tract
PCTOWNHOMEpercentage of people in each tract owning their own home
PCTAGE65Ppercentage of people in each tract aged 65 or more
Zransformed propoprtions
AVGIDISTaverage distance between centroid and TCE sites
PEXPOSURE"exposure potential": inverse distance between each census tract centroid and the nearest TCE site, IDIST, transformed via log(100*IDIST)
The examples section shows how the DBF files from the book website for Chapter 9 were converted into the nydata data frame and the listw_NY spatial weights list.
http://web1.sph.emory.edu/users/lwaller/ch9index.htm
Waller, L. and C. Gotway (2004) Applied Spatial Statistics for Public Health Data. New York: John Wiley and Sons.
1 2 3 4 5 6 7 8 9 10 11  | ## NY leukemia
library(foreign)
nydata <- read.dbf(system.file("etc/misc/nydata.dbf", package="spdep")[1])
coordinates(nydata) <- c("X", "Y")
nyadjmat <- as.matrix(read.dbf(system.file("etc/misc/nyadjwts.dbf",
 package="spdep")[1])[-1])
ID <- as.character(names(read.dbf(system.file("etc/misc/nyadjwts.dbf",
 package="spdep")[1]))[-1])
identical(substring(ID, 2, 10), substring(as.character(nydata$AREAKEY), 2, 10))
nyadjlw <- mat2listw(nyadjmat, as.character(nydata$AREAKEY))
listw_NY <- nb2listw(nyadjlw$neighbours, style="B")
 | 
Loading required package: sp
Loading required package: Matrix
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Field name: 'Z600701220' changed to: 'Z600701220.1'
Field name: 'Z600701270' changed to: 'Z600701270.1'
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Field name: 'Z600701330' changed to: 'Z600701330.1'
Field name: 'Z605303010' changed to: 'Z605303010.1'
Field name: 'Z605303010' changed to: 'Z605303010.2'
Field name: 'Z605303040' changed to: 'Z605303040.1'
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Field name: 'Z606701110' changed to: 'Z606701110.1'
Field name: 'Z606701120' changed to: 'Z606701120.1'
Field name: 'Z606701120' changed to: 'Z606701120.2'
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Field name: 'Z606701140' changed to: 'Z606701140.1'
Field name: 'Z606701520' changed to: 'Z606701520.1'
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[1] TRUE
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