Transform data for repeated measures
On Thu, Aug 27, 2009 at 6:37 PM, Richardson,
Patrick<Patrick.Richardson at vai.org> wrote:
I have a dataset that I'm trying to rearrange for a repeated measures analysis: It looks like: patient basefev1 fev11h fev12h fev13h fev14h fev15h fev16h fev17h fev18h drug 201 ? ? 2.46 ? 2.68 ? 2.76 ? 2.50 ? 2.30 ? 2.14 ? 2.40 ? 2.33 ? 2.20 ? ?a 202 ? ? 3.50 ? 3.95 ? 3.65 ? 2.93 ? 2.53 ? 3.04 ? 3.37 ? 3.14 ? 2.62 ? ?a 203 ? ? 1.96 ? 2.28 ? 2.34 ? 2.29 ? 2.43 ? 2.06 ? 2.18 ? 2.28 ? 2.29 ? ?a 204 ? ? 3.44 ? 4.08 ? 3.87 ? 3.79 ? 3.30 ? 3.80 ? 3.24 ? 2.98 ? 2.91 ? ?a And I want to make it look like: Patient ?FEV ?time ?drug 201 ? ? ? ? 2.46 ? ?0 ? ? ? ? a 201 ? ? ? ? 2.68 ? ?1 ? ? ? ? a 201 ? ? ? ? 2.76 ? ?2 ? ? ? ? a 201 ? ? ? ? 2.50 ? ?3 ? ? ? ? a And so on . . . . . There would be 9 "time" and drug is a factor variable. I know there is a way to do this in R but I cannot remember the function. I've looked at the transpose function in (base) but that doesn't seem to be what I want. Can something like this be done easily from within package functions or would it require writing something custom? Another program would use something like the transpose procedure, but I'm trying to stay away from that program.
To give a concrete example of what using the reshape package would
look like: (thanks to David for making your example easily
reproducible)
resp.df <- read.table(textConnection("patient basefev1 fev11h fev12h
fev13h fev14h fev15h fev16h fev17h fev18h drug
201 2.46 2.68 2.76 2.50 2.30 2.14 2.40 2.33 2.20 a
202 3.50 3.95 3.65 2.93 2.53 3.04 3.37 3.14 2.62 a
203 1.96 2.28 2.34 2.29 2.43 2.06 2.18 2.28 2.29 a
204 3.44 4.08 3.87 3.79 3.30 3.80 3.24 2.98 2.91
a"), header=TRUE)
closeAllConnections()
library(reshape)
# Identify the variables controlled by your experimental design:
stk.resp <- melt(resp.df, id = c("patient", "drug"))
stk.resp$time <- as.numeric(gsub("[^0-9]", "", stk.resp$variable))
Hadley