If you have 2 cross classifying variables you can use rowSums
and colSums
to produce margin totals on an xtabs
output. But how can it be done if you have 3 classifying variables (ie margin totals in each sub table)?
views:
119answers:
4
+1
A:
(if I understand correctly) You could use ddply:
ff <- data.frame(f1=c("a", "b", "b", "b", "b", "b", "b"), f2=c("p", "p", "p", "q", "q", "q", "q"), f3=c("x","x","x","x","y", "y", "y"), val=c(1:7))
ddply(ff, .(f1), numcolwise(sum))
ddply(ff, .(f2), numcolwise(sum))
ddply(ff, .(f3), numcolwise(sum))
momobo
2010-04-02 13:41:01
+1
A:
The general approach is to use the apply
function, but specifically for totals the margin.table
function might be more convenient:
#create 3 factors
a <- gl(2,4, length=20)
b <- gl(3,2, length=20)
d <- gl(4,2, length=20)
# table
tt <- xtabs(~a+b+d)
# marginal sums
margin.table(tt, 1)
apply(tt, 1, sum) #same answer
#multi-way margins
margin.table(tt, 1:2)
apply(tt, 1:2, sum) #same answer
Aniko
2010-04-02 13:41:53
A:
Comments aren't working above. Thanks for the answers, but they didn't do what I was expecting - individual totals in each subgrouping.
After a little digging around, I found that the xtabs output in this case is a 3 dimensional array, and wrote the following function to achieve my desired result (note its incomplete, but works for column totals so far):
xtabTotals <- function(tabs,margin=1)
# takes a 3 dimensional xtabs array and performs margin total on each sub table
# only doing column margins so far
{
out <- array(0,dim(tabs)+c(1,0,0))
dnout <- dimnames(tabs)
dnout[[1]] <- c(dnout[[1]],"Total")
dimnames(out) <- dnout
for (i in 1:dim(tabs)[3])
{
out[,,i] <- rbind(tabs[,,i],colSums(tabs[,,i]))
}
out
}
James
2010-04-02 15:27:46
I clearly did not understand what you wanted, and I still don't even looking at your function. Perhaps you are looking for `addmargins`?
Aniko
2010-04-02 21:23:09
Yes this is exactly what I want, thanks!
James
2010-04-07 09:59:23
+1
A:
If you are not tied to xtabs, the Deducer package has some nice functions for contingency tables:
> a <- gl(2,4, length=20)
> b <- gl(3,2, length=20)
> d <- rnorm(20)>0
> dat <- data.frame(a,b,d)
> tables<-contingency.tables(
+ row.vars=a,
+ col.vars=b,
+ stratum.var=d,data=dat)
> tables
================================================================================
==================================================
========== Table: a by b ==========
| -- Stratum = FALSE --
| b
a | 1 | 2 | 3 | Row Total |
-----------------------|-----------|-----------|-----------|-----------|
1 Count | 2 | 2 | 1 | 5 |
Row % | 40.000% | 40.000% | 20.000% | 55.556% |
Column % | 40.000% | 100.000% | 50.000% | |
Total % | 22.222% | 22.222% | 11.111% | |
-----------------------|-----------|-----------|-----------|-----------|
2 Count | 3 | 0 | 1 | 4 |
Row % | 75.000% | 0.000% | 25.000% | 44.444% |
Column % | 60.000% | 0.000% | 50.000% | |
Total % | 33.333% | 0.000% | 11.111% | |
-----------------------|-----------|-----------|-----------|-----------|
Column Total | 5 | 2 | 2 | 9 |
Column % | 55.556% | 22.222% | 22.222% | |
| -- Stratum = TRUE --
| b
a | 1 | 2 | 3 | Row Total |
-----------------------|-----------|-----------|-----------|-----------|
1 Count | 2 | 2 | 3 | 7 |
Row % | 28.571% | 28.571% | 42.857% | 63.636% |
Column % | 66.667% | 50.000% | 75.000% | |
Total % | 18.182% | 18.182% | 27.273% | |
-----------------------|-----------|-----------|-----------|-----------|
2 Count | 1 | 2 | 1 | 4 |
Row % | 25.000% | 50.000% | 25.000% | 36.364% |
Column % | 33.333% | 50.000% | 25.000% | |
Total % | 9.091% | 18.182% | 9.091% | |
-----------------------|-----------|-----------|-----------|-----------|
Column Total | 3 | 4 | 4 | 11 |
Column % | 27.273% | 36.364% | 36.364% | |
================================================================================
Ian Fellows
2010-04-02 16:52:14