On May 9, 2009, at 4:53 PM, JC wrote:
I am very new to R. I have some data from a CVS stored in vdata with 4 columns labeled: X08, Y08, X09, Y09. I have created two new "columns" like so: Z08 <- (vdata$X08-vdata$Y08) Z09 <- (vdata$X09-vdata$Y09) I would like to use chisq.test for each "row"
Of what?
and output the p-value for each in a stored variable. I don't know how to do it. Can you help? so far I have done it for one row (but I want it done automatically for all my data): chidata=rbind(c(vdata$Y08[1],Z08[1]),c(vdata$Y09[1],Z09[1]))
Maybe I am dense, but I cannot figure out what hypothesis is being tested.
results <- chisq.test(chidata) results$p.value
Generally using apply(vdata, 1, ..... would give you a row by row computation.
I tried removing the [1] and the c() but that didn't work... Any ideas?
As Jim Holtman's tag line says: "What problem are you trying to solve?" David Winsemius, MD Heritage Laboratories West Hartford, CT ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
