I have a data.frame with ~250 observations (rows) in each of ~50
categories (columns). I would like to perform t.tests on subsets of
observations within each column, with the subsets according to index
vectors contained in other columns of the data.frame.
My data.frame looks something like this:
x<-data.frame(matrix(rnorm(200,mean=5,sd=.5),nrow=20))
colnames(x)<-c("site", "status", "X1", "X2", "X3", "X4", "X5", "X6",
"X7", "X8")
x$site<-as.factor(rep(c("A", "A", "B", "B", "C"), 4))
x$status<-as.factor(rep(c("D", "L"), 10))
I want to do t.tests on the numeric observations within the data.frame
by "site" and by "status":
t.test(x[x$site == "A" & x$status =="D",]$X1, x[x$site == "A" & x
$status =="L",]$X1)
t.test(x[x$site == "B" & x$status =="D",]$X1, x[x$site == "B" & x
$status =="L",]$X1)
t.test(x[x$site == "C" & x$status =="D",]$X1, x[x$site == "C" & x
$status =="L",]$X1)
t.test(x[x$site == "A" & x$status =="D",]$X2, x[x$site == "A" & x
$status =="L",]$X2)
t.test(x[x$site == "B" & x$status =="D",]$X2, x[x$site == "B" & x
$status =="L",]$X2)
t.test(x[x$site == "C" & x$status =="D",]$X2, x[x$site == "C" & x
$status =="L",]$X2)
etc...
I know I must be able to do this more efficently using a loop and one
of the apply functions, e.g. something like this:
k=length(levels(x$site))
for (i in 1:k)
{
site<-levels(x$site)[i]
x1<-x[x$site == site, ]
results[i]<-apply(x1, 2, function(x1) {t.test(x1[x1$status == "D",],
x1[x1$status == "L",])})
results
}
But I can't figure out how to do the apply function correctly...
Also wonder whether there's a way to use the apply-type function and
aviod the loop all together.
Thanks in advance!
Ali
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