tags:

views:

119

answers:

4

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)?

+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
+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
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
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
Yes this is exactly what I want, thanks!
James
+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