Rubén Roa-Ureta wrote:
Jon A wrote:
Hello,
I have a dataset with a continuous independent variable (fish length,
range:
30-150 mm) and a binary response (foraging success, 0 or 1). I want to
discretize fish length into 5 mm bins and give the proportion of
individuals
who successfully foraged in each each size bin. I have used the cut
function
to discretize the length values into my desired bins, but I can't
figure out
how to manipulate my response data in terms of the levels I've
created. Any
advice on how to achieve my task?
Thanks in advance.
You have the option of using catspec.
Here is another, more transparent solution, using hist().
lb <- 30
ub <- 150
bk <- 5
x <- data.frame(cbind(runif(1000,lb,ub),rbinom(1000,1,0.75)))
x$X3 <- cut(x$X1,breaks=(ub-lb)/bk,labels=FALSE)
y <-
data.frame(cbind(hist(x$X1,breaks=(ub-lb)/bk,plot=FALSE)$breaks[-1],hist(x$X1,breaks=(ub-lb)/bk,plot=FALSE)$counts,0))
for (i in 1:length(y$X1)) {
for (j in 1:length(x$X1)) {
if(identical(x$X3[j],i)) y$X3[i] <- y$X3[i]+x$X2[j]
}
}
sum(x$X2) #check that counting was correct
sum(y$X3)
y$X4 <- ifelse(y$X3 > 0,y$X3/y$X2,NA)
plot(y$X1,y$X4,pch=19)
abline(v=hist(x$X1,breaks=(ub-lb)/bk,plot=FALSE)$breaks)
BTW, if you add the line below,
text(x=y$X1,y=y$X4+.01,format(y$X2),cex=.5)
you show the sample size at each proportion.
R.
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