On Nov 29, 2010, at 9:35 AM, David Freedman wrote:
Hi - I apologize for the 2nd post, but I think my question from a
few weeks
ago may have been overlooked on a Friday afternoon.
I might be missing something very obvious, but is it widely known
that the
aggregate function handles missing values differently depending if a
data
frame or a formula is the first argument ?
I'm not sure if it is widely known, but it is certainly suggested by
the documentation for aggregate, since aggregate.data.frame has
different defaults than aggregate.formula. See the Usage section at
the very top of ?aggregate.
For example,
(d<- data.frame(sex=rep(0:1,each=3),
wt=c(100,110,120,200,210,NA),ht=c(10,20,NA,30,40,50)))
x1<- aggregate(d, by = list(d$sex), FUN = mean);
names(x1)[3:4]<- c('mean.dfcl.wt','mean.dfcl.ht')
x2<- aggregate(cbind(wt,ht)~sex,FUN=mean,data=d);
names(x2)[2:3]<- c('mean.formcl.wt','mean.formcl.ht')
cbind(x1,x2)[,c(2,3,6,4,7)]
The output from the data.frame class has an NA if there are missing
values
in the group for the variable with missing values. But, the formula
class
output seems to delete the entire row (missing and non-missing
values) if
there are any NAs. Wouldn't one expect that the 2 forms (data frame
vs
formula) of aggregate would give the same result?
thanks very much
david freedman, atlanta
--
David Winsemius, MD
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.
