
#Would like to create a cross-table (Region, district, response) and 
#(Region, district, cost. The flat table function does not look so good 
region   <- c("A","A","A","A","B","B", "B", "B", "C","C", "C", "C") 
district <- c("d","d","e","e","f","f", "g", "g", "h","h", "i", "j") 
response <- c("yes", "no", "yes", "yes", "no", "yes", "yes", "no", "yes", "no", "yes","no")
cost  <-  runif(12, 5.0, 9)
var <- c("region", "response", "district")
data <- data.frame(region, district, response, cost)
var1 <- c("region", "district", "response")
var2 <- c("region", "district", "cost")
data1 <- data[var1]
#This look okay
with(data, aggregate(x=cost, by=list(region, district), FUN="mean"))
#This does not look good 
#How do i remove the NaN or create a better one
prop.table(ftable(data1, exclude = c(NA, NaN)), 1)
prop.table(ftable(xtabs(~region + district+ response, data=data)),1)


Peter Maclean
Department of Economics
UDSM
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