Hi Bertolt,
by(test,INDICES=test$groupID,FUN=mean)
And today's a holiday in Switzerland, so stop working already ;-)
HTH
Stephan
Bertolt Meyer schrieb:
Dear R users,
I have a newbie-question that I couldn't resolve after reading through
several pieces of documentation and searching the archive.
I have a data.frame containing experimental data from a group experiment
in psychology. Each line represents a single participant, but
participants were assigned to groups of three or four persons. One
variable indicates each participants' group number (groupID). For a
large number of variables, I would like to obtain the mean group value.
I figured I use tapply() in the fashion of tapply(variable, groupID,
mean), but that would be a tiresome task for my 150 variables. I am thus
looking for a way to obtain a data.frame that contains one row for each
group with the group-mean variables as columns.
Example:
> test <- as.data.frame(cbind(c(rep(1,5),rep(2,5)), rnorm(10), rnorm(10)))
> names(test)[1] <- "groupID"
> test
groupID V2 V3
1 1 -0.82990860 -0.61778919
2 1 -0.01379452 0.64609053
3 1 -2.64990839 -1.00570627
4 1 -0.07903878 -0.70864441
5 1 0.61483071 -1.32039565
6 2 -0.18913937 1.38490710
7 2 -0.60017953 0.15893421
8 2 -0.99901931 0.05963436
9 2 -1.46759515 0.35040283
10 2 -0.44650422 -0.08713162
> tapply(test$V2, test$groupID, mean)
1 2
-0.5915639 -0.7404875
> tapply(test$V3, test$groupID, mean)
1 2
-0.6012890 0.3733494
I am now looking for something that gives me
groupID V2 V3
1 1 -0.5915639 -0.6012890
2 2 -0.7404875 0.3733494
Any ideas?
Thank you very much,
Bertolt
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