Hi,
I am not perfectly sure what you want to do, but here is what I would do
to maintain good/bad ratio in the sample (as Daniel posted, split the
data and sample from the groups):
df <- data.frame(V1 = 1:400, V2 = c(rep("good",360), rep("bad",40)))
isGood <- which(df$V2=="good")
isBad <- which(df$V2=="bad")
sampleGood <- df[sample(isGood, replace=TRUE),]
sampleBad <- df[sample(isBad, replace=TRUE),]
summary(rbind(sampleGood, sampleBad))
Please include a more specific example with test data (for "final" in
this case) next time.
Best regards,
Andreas
taby gathoni schrieb:
Dear all,
i have a dataset of about 400 records , with a variable that has two levels 40
bad and 360 good among other variables,how do i come up with10 random samples
that have the composition of as the main sample but maintaining the 40 bad 360
good with replacement, i recently discovered that my random samples generated
dont maintain the ratio. My code is as :
mysample <- final[sample(1:nrow(final), 400,replace=TRUE),]
does not give me the ratio of 40 bad and 360 good can anyone give me some
pointers please?
Thanks,
Taby
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Andreas Borg
Medizinische Informatik
UNIVERSITÄTSMEDIZIN
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