All,
For data consisting of serial measurements on subjects, one may use the
aggregate function to say compute the peak response for each subject for
each design condition. Is there a way to alter this or another one-liner to
also retain the time at which the peak occurred and thus avoid writing a
doing this via a loop? I suppose one could attempt to employ the split
function but that's probably no simpler than employing a loop. Sample code
below:
data = expand.grid(time = seq(1,6), subject = seq(1,20), treatment =
c("placebo", "drug"))
data.ex = cbind(y = rnorm(dim(data)[1], 5, 1), data.ex)
data.peak = aggregate(data.ex[c(1)], data.ex[c(3,4)], max)
## this provides the peak of each subject on each treatment, but time is
## lost. Including time in the statement doesn't help clearly as then
## the peak of all the times will be calculated
David
--------------------------------------
David Afshartous, Ph.D.
Research Assistant Professor
University of Miami, Miller School of Medicine
Division of Clinical Pharmacology
1500 N.W. 12th Avenue, 15th Floor West
Miami, Florida 33136
E-mail: afs...@med.miami.edu
Phone: +1 305-243-1549
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