Hi:
Does this work?
library(plyr)
ddply(tmp, .(trial, Gender), transform, rankscore = rank(score))
score trial Gender rankscore
1 1 1 M 1
2 2 1 M 2
3 3 1 F 1
4 4 1 F 2
5 4 2 M 2
6 3 2 M 1
7 2 2 F 2
8 1 2 F 1
Alternatively, you could get the 'wide form' with
aggregate(score ~ trial + Gender, data = tmp, FUN = rank)
trial Gender score.1 score.2
1 1 M 1 2
2 2 M 2 1
3 1 F 1 2
4 2 F 2 1
HTH,
Dennis
On Fri, Apr 29, 2011 at 12:26 PM, Doran, Harold <hdo...@air.org> wrote:
> Suppose I have data such as
>
> tmp <- data.frame(score = c(1,2,3,4, 4,3,2,1), trial = gl(2,4), Gender =
> gl(2,2,8, labels=c('M', 'F')))
>
> Now I would like to compute a rank on the variable score conditional on trial
> and gender. I could do
>
> res <- with(tmp, tapply(score, list(Gender, trial), rank))
> res[,1]
> res[,2]
>
> and then finagle a way to create a new variable in the dataframe tmp that has
> these ranks associated with the correct rows. But, perhaps there is a better
> way. Any suggestions?
>
> [[alternative HTML version deleted]]
>
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