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 ? 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$sex), FUN = mean);
names(x1)[3:4]<- c('mean.dfcl.wt','mean.dfcl.ht')
x2<- aggregate(cbind(wt,ht)~sex,FUN=mean,data=d);
names(x2)[2:3]<- c('mean.formcl.wt','mean.formcl.ht')
cbind(x1,x2)[,c(2,3,6,4,7)]
The output from the data.frame class has an NA if there are missing values
in the group for the variable with missing values. But, the formula class
output seems to delete the entire row (missing and non-missing values) if
there are any NAs. Wouldn't one expect that the 2 forms (data frame vs
formula) of aggregate would give the same result?
thanks very much
david freedman, atlanta
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On Nov 29, 2010, at 9:35 AM, David Freedman wrote:> > Hi - I apologize for the 2nd post, but I think my question from a > few weeks > ago may have been overlooked on a Friday afternoon. > > I might be missing something very obvious, but is it widely known > that the > aggregate function handles missing values differently depending if a > data > frame or a formula is the first argument ?I'm not sure if it is widely known, but it is certainly suggested by the documentation for aggregate, since aggregate.data.frame has different defaults than aggregate.formula. See the Usage section at the very top of ?aggregate.> For example, > > (d<- data.frame(sex=rep(0:1,each=3), > wt=c(100,110,120,200,210,NA),ht=c(10,20,NA,30,40,50))) > x1<- aggregate(d, by = list(d$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
On 2010-11-29 06:35, 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 ? 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? >Wasn't there some discussion of this not long ago? Maybe I'm getting senile. Anyway, as David W. points out, the defaults differ. Here's how you can get the same result from both methods: 1. use na.action = na.pass in aggregate.formula; this will duplicate your x1 result. 2. use d <- d[complete.cases(d), ] in your x1 calculation; this will duplicate your x2 result. Peter Ehlers> thanks very much > david freedman, atlanta > > > >
Thanks for the information. There was a discussion of different results obtained with the formula and data.frame methods for a paired t-test -- there are many threads, but one is at http://r.789695.n4.nabble.com/Paired-t-tests-td2325956.html#a2326291 david freedman -- View this message in context: http://r.789695.n4.nabble.com/data-frame-and-formula-classes-of-aggregate-tp3063668p3064177.html Sent from the R help mailing list archive at Nabble.com.