long format - find age when another variable is first 'high'

Tue, May 26, 2009 9:42 AM

From: r-help-bounces at r-project.org 
[mailto:r-help-bounces at r-project.org] On Behalf Of Marc Schwartz
Sent: Monday, May 25, 2009 6:52 AM
To: David Freedman
Cc: r-help at r-project.org
Subject: Re: [R] long format - find age when another variable 
is first 'high'


On May 25, 2009, at 7:45 AM, David Freedman wrote:

Dear R,

I've got a data frame with children examined multiple times and at  
various
ages.  I'm trying to find the first age at which another variable
(LDL-Cholesterol) is >= 130 mg/dL; for some children, this

may never

happen.
I can do this with transformBy and ddply, but with 10,000 different
children, these functions take some time on my PCs - is there a  
faster way
to do this in R?  My code on a small dataset follows.

Thanks very much, David Freedman

d<-data.frame(id=c(rep(1,3),rep(2,2), 
3),age=c(5,10,15,4,7,12),ldlc=c(132,120,125,105,142,160))
d$high.ldlc<-ifelse(d$ldlc>=130,1,0)
d
library(plyr)
d2<-ddply(d,~id,transform,plyr.minage=min(age[high.ldlc==1]));
library(doBy)
d2<-transformBy(~id,da=d2,doby.minage=min(age[high.ldlc==1]));
d2

The first thing that I would do is to get rid of records that 
are not  
relevant to your question:

> d

id age ldlc high.ldlc
1  1   5  132         1
2  1  10  120         0
3  1  15  125         0
4  2   4  105         0
5  2   7  142         1
6  3  12  160         1


# Get records with high ldl
d.new <- subset(d, ldlc >= 130)

 > d.new

id age ldlc high.ldlc
1  1   5  132         1
5  2   7  142         1
6  3  12  160         1


That will help to reduce the total size of the dataset, perhaps  
substantially. It will also remove entire subjects that are not  
relevant (eg. never have LDL >= 130).

Then get the minimum age for each of the remaining subjects:

 > aggregate(d.new$age, list(id = d.new$id), min)

If the dataset has a lot of rows you can save more time
by replacing the call to aggregate(age,id,min) by code that sorts
the filtered data by 'id' then breaking ties with 'age', and
then picking out the elements just after a change in the
value of 'id':
    f <- function(d) {
         dSorted <- d[ order(d$id,d$age),]
         n <- length(d$id) # or nrow(d)
         dSorted[   c(TRUE, dSorted$id[-1] != dSorted$id[-n]), ]
    }
    f(d.new) # or f(d[d$ldlc>=130,]) to avoid leaving around the temp
variable.
If you know your dataset is already sorted in this way, you just
need only the last line of that function.

Bill Dunlap
TIBCO Software Inc - Spotfire Division
wdunlap tibco.com

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long format - find age when another variable is first 'high'

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